WO2008066129A1 - Testing apparatus, testing method, image pickup testing system, color filter manufacturing method, and testing program - Google Patents

Abstract

An image analyzing apparatus (100), which is one of testing apparatuses according to the present invention, tests a color filter substrate (330) based on picked-up image data obtained by imaging a light-irradiated to-be-tested surface of the color filter substrate (330). The image analyzing apparatus (100) comprises a one-dimensional projection processing circuit (110) that performs a one-dimensional projection processing of light distribution information included in the picked-up image data with an arbitrary direction used as a projecting direction; and a period analysis processing circuit (120) that performs a period analysis of the light distribution information having been subjected to the one-dimensional projection processing by the one-dimensional projection processing circuit (110). In this way, the period of the light distribution in the picked-up image in the projecting direction can be determined from a period analysis result, thereby making it possible to determine whether there exists any periodicity for unevenness (stripe unevenness) occurring on the surface of the display member of the color filter substrate (330) or the like that is a tested object.

Description

 Specification

 Inspection device, inspection method, imaging inspection system, color filter manufacturing method, inspection program

 Technical field

 The present invention relates to an inspection apparatus for inspecting display members such as color filters.

 Background art

 In recent years, display devices such as televisions and monitors have become thinner and larger, and the demand for such devices has increased. Along with this, higher quality display performance is required more than ever.

 [0003] Among the components that make up a display device, a color filter for color display is one of the important components that affect display quality. For this reason, the quality required for color filters has become higher.

 [0004] Further, since the specific cost of the color filter is high! /, It is required to improve the yield of the color filter and to reduce the production cost per sheet.

 [0005] Recently, a method for forming a color filter by an ink jet method has attracted attention! In this forming method, the ink is formed by ejecting R (red), G (green) and Β (blue) ink from the nozzles of the inkjet head to each picture element. The characteristics of the ink jet method are that the number of processes is reduced and the waste of ink is reduced, so that the process can be shortened and the cost can be reduced.

 [0006] However, when forming a color filter in the ink jet system, stripes are particularly likely to occur. As a result, display quality may deteriorate or defective products may appear.

[0007] As a technique for inspecting this stripe unevenness, for example, the technique described in Patent Document 1 irradiates light at a predetermined inclination angle, images the film surface irradiated with light, and analyzes captured image information. The brightness difference between each undulation is calculated, and the unevenness is detected by estimating the film thickness difference between each undulation on the film surface. Patent Document 1: Japanese Published Patent Publication “Japanese Unexamined Patent Publication No. 2006-184125 (Publication Date: July 13, 2006)”

 Disclosure of the invention

 [0008] By the way, among the uneven stripes on the color filter, due to the human visual characteristics, the uneven stripes that are generated with periodicity are particularly noticeable. Therefore, the uneven stripes with periodicity are not preferable in terms of the quality of the display device.

 [0009] For this reason, it is very important in the color filter inspection process to determine whether or not the observed uneven stripe has periodicity. In addition, if it is known that the stripes have periodicity, it is easier to identify the cause of the stripes, and when producing color filters, the cause of the stripes can be fed back to improve quality.

 [0010] However, the color filter inspection apparatus disclosed in Patent Document 1 can detect stripes on the color finerator but cannot detect the periodicity of the stripes. For this reason, the cause of the occurrence of streak cannot be identified, and when manufacturing a color filter, the cause of the occurrence of streak cannot be fed back, so it is difficult to improve quality.

 [0011] The present invention has been made in view of the above problems, and an object of the present invention is the presence or absence of periodicity of unevenness (straight lines) generated on the surface of a display member such as a color filter that is an object to be inspected. This is to realize an inspection device that can make this determination.

 [0012] In order to solve the above problems, an inspection apparatus according to the present invention performs inspection of a display member based on captured image data obtained by imaging an inspection symmetry plane irradiated with light on the display member. A one-dimensional projection processing unit that performs one-dimensional projection processing with respect to the light distribution information included in the captured image data, with an arbitrary direction as a projection direction, and the one-dimensional projection processing unit. It comprises a periodic analysis processing means for performing periodic analysis of the processed light distribution information.

[0013] Further, in order to solve the above-described problem, the inspection method according to the present invention is based on captured image data obtained by imaging the inspection symmetry plane irradiated with light of the display member. In the inspection method for performing an inspection, a first step of performing one-dimensional projection processing with an arbitrary direction as a projection direction on the light distribution information included in the captured image data, and the first And a second step of performing periodic analysis of the light distribution information after the one-dimensional projection processing obtained by the step!

 [0014] According to the above configuration, the one-dimensional projection processing means performs one-dimensional projection processing on the two-dimensional light distribution information in the captured image data, thereby obtaining light distribution information in the projection direction in the captured image. be able to. Then, by performing periodic analysis of the light distribution information in the projection direction in the captured image by the periodic analysis processing means, the period of the light distribution in the projection direction in the captured image can be determined from the periodic analysis result.

 [0015] With this, it is possible to determine the presence or absence of the periodicity of stripe unevenness if the direction of occurrence of uneven stripes on the surface of the display member is the projection direction described above.

 [0016] For example, when the display member is a color filter, it is possible to specify a non-uniform stripe having a periodicity among the non-uniform stripes generated on the surface of the color filter. A high-quality color filter can be obtained by changing the manufacturing process so as to eliminate the uneven stripes.

 [0017] Further, the period analysis processing means may perform a Fourier transform on the light distribution information.

 [0018] According to the above configuration, the periodic analysis processing unit obtains a periodic function of the light distribution information by performing Fourier transform on the light distribution information subjected to the one-dimensional projection processing by the one-dimensional projection processing unit. be able to.

[0019] If the obtained periodic function is graphed, for example, the operator can easily determine the presence or absence of periodic irregularities on the surface of the display member visually.

[0020] Further, since the periodic function is obtained by using Fourier transform, the periodic function force, the smoothing period, and the like can be obtained.

[0021] Thus, when manufacturing the display member, the period of the stripe unevenness is fed back.

Therefore, it is possible to identify the cause of the occurrence of uneven stripes, and as a result, it is possible to provide a high-quality display member.

[0022] The inspection apparatus having the above-described configuration further includes a finoletering processing unit that performs filtering processing on the light distribution information subjected to the one-dimensional projection processing by the one-dimensional projection processing unit using a filter of an arbitrary size. The period analysis processing means is connected to the filtering processing means. Therefore, periodic analysis of the filtered light distribution information may be performed.

 [0023] Further, in the inspection method having the above-described configuration, the light distribution information after the one-dimensional projection processing obtained by the first step is further obtained between the first step and the second step. A filtering process step for performing a filtering process with a filter of an arbitrary size is provided, and the second step performs a periodic analysis of the light distribution information after the filtering process obtained by the filtering process step. Good.

 [0024] According to the above configuration, the light distribution information subjected to the one-dimensional projection processing by the filtering processing means is subjected to filtering processing by a filter of an arbitrary size, so that the analysis means in the subsequent stage can perform filtering from the filter size. Therefore, it is possible to suppress the period of stripes with a large width, and to extract the period of stripes with a width smaller than the filter size.

 That is, by changing the filter size in the filtering processing circuit, it becomes possible to extract the period of stripes with various widths, so that it is possible to emphasize the period of stripes with a necessary width S, and as a result. It is possible to easily determine the presence or absence of periodicity of stripes.

 [0026] The filtering processing in the filtering processing circuit is preferably a morphology processing.

 [0027] The filtering processing in the filtering processing circuit is preferably smoothing processing.

 [0028] The filtering processing circuit includes a smoothing processing circuit that performs smoothing processing on the light distribution information that has been subjected to the one-dimensional projection processing by the one-dimensional projection processing means, and smoothing by the smoothing processing circuit. A morphology processing circuit that performs a morphology process on the processed light distribution information may be provided, and the light distribution information subjected to the morphology process by the morphology processing circuit may be output to the period analysis processing means.

 [0029] Further, the filtering processing circuit includes a morphology processing circuit that performs morphology processing on the light distribution information that has been one-dimensionally projected by the one-dimensional projection processing means, and light that has undergone the morphology processing by the morphology processing circuit. A smoothing processing circuit that performs a smoothing process on the distribution information may be provided, and the light distribution information smoothed by the smoothing processing circuit may be output to the periodic analysis processing means.

[0030] According to the above configuration, the light component subjected to the one-dimensional projection processing by the one-dimensional projection processing means. By applying two types of filtering processing, which are different in smoothing processing and morphology processing, to the fabric information, even if it is a period of stripes with a width that could not be filtered or emphasized, it can be compensated on the other side. it can. As a result, it is possible to easily determine the presence or absence of stripe irregularity and to specify the stripe unevenness period.

 [0031] The inspection apparatus can be applied to an imaging inspection system as described below.

 That is, in the imaging inspection system of the present invention, the illumination device that irradiates light on the front surface or the back surface of the display member, and the display member is irradiated with the light in a state irradiated with light! /, And an inspection apparatus having the above-described configuration for inspecting the display member based on captured image data imaged by the imaging apparatus. RU

 [0033] The color filter manufacturing method of the present invention is a color filter manufacturing method for manufacturing a color filter by a color filter manufacturing apparatus in order to solve the above-described problems, and the period according to the inspection method described above. Only color filters determined to be non-defective as a result of the analysis are used in the manufacturing process after the inspection process in the color filter manufacturing apparatus.

 [0034] According to the above configuration, in the inspection process included in the color filter manufacturing process, the color filter determined as a non-defective product as a result of the periodic analysis (determined that the stripes have no periodicity). Since only the color filter) is used in the color filter manufacturing process after the inspection process, the color filter having a stripe irregularity does not go through the process after the inspection process. Therefore, since the defective color filter is not produced in vain, the yield S of the color filter can be improved and the manufacturing cost of the color filter can be reduced.

 [0035] A color filter manufacturing method of the present invention is a color filter manufacturing method for manufacturing a color filter by a color filter manufacturing apparatus in order to solve the above-described problems, and is a result of periodic analysis by the above-described inspection method. When a color filter determined to be a defective product is generated, information indicating that the defective product is generated is transmitted to the color filter manufacturing apparatus.

[0036] According to the above configuration, in the inspection process included in the color filter manufacturing process! As a result of the analysis, if a color filter that was determined to be defective (a color filter that was determined to have periodicity in stripes) occurred! /, The information was transmitted to the color filter manufacturing equipment. It is possible to take measures such as stopping the color filter production line on the color filter production equipment side. Therefore, since defective color filters are not produced unnecessarily, the yield of color filters can be improved and the manufacturing cost of color filters can be reduced.

Brief Description of Drawings

FIG. 1, showing an embodiment of the present invention, is a block diagram showing a main configuration of an image analysis apparatus.

 2 is a diagram showing an outline of an imaging inspection apparatus using the image analysis apparatus shown in FIG.

FIG. 3 is a diagram showing a manufacturing process of a color filter as an object to be inspected.

4 is a diagram showing an image obtained by imaging a color filter by the imaging apparatus of the imaging inspection apparatus shown in FIG. 2.

 [Fig.5] One-dimensional projection processing is performed from the two-dimensional luminance distribution information obtained from the image shown in Fig.4.

FIG. 6 is a graph showing the result of performing Fourier transform on the data of the graph shown in FIG.

 FIG. 7 is a flowchart showing a process flow of a manufacturing process of a color filter substrate.

FIG. 8, showing another embodiment of the present invention, is a block diagram showing a main configuration of an image analysis apparatus.

 FIG. 9 (a) is a graph showing the state of morphology processing by the morphology processing circuit of the image analysis apparatus shown in FIG.

 [Fig. 9 (b)] is a graph showing the state of morphology processing by the morphology processing circuit of the image analysis device shown in Fig. 8.

 FIG. 10 is a flowchart showing a flow of an inspection method using the image analysis apparatus shown in FIG.

FIG. 11 is a graph showing the result of the morphology processing with the filter size set to fl pixels with respect to the result of the one-dimensional projection processing in the image analysis apparatus shown in FIG. FIG. 12 is a graph showing the result of performing Fourier transform on the data in the graph of FIG.

FIG. 13 is a graph showing the result of the morphology processing with the filter size set to f2 pixels with respect to the result of the one-dimensional projection processing in the image analysis apparatus shown in FIG.

 FIG. 14 is a graph showing the result of performing Fourier transform on the data of the graph of FIG.

FIG. 15, showing still another embodiment of the present invention, is a block diagram showing a main configuration of an image analyzing apparatus.

 FIG. 16 is a graph showing the result of smoothing processing with the finalizer size set to f3 pixels with respect to the result of the one-dimensional projection processing in the image analysis apparatus shown in FIG.

 FIG. 17 is a graph showing the result of performing a Fourier transform on the data in the graph of FIG.

FIG. 18 shows still another embodiment of the present invention, and is a block diagram showing a main configuration of an image analysis apparatus.

 FIG. 19 is a graph showing the result of morphological processing on the data of the graph of FIG. 16 with a filter size of f2 pixels.

 FIG. 20 is a graph showing the result of performing Fourier transform on the data in the graph of FIG.

BEST MODE FOR CARRYING OUT THE INVENTION

 [0038] An embodiment of the present invention will be described as follows.

 [0039] In the present invention, the display member refers to a member that is used in an image display device and transmits or reflects light or both.

 [0040] In this embodiment, a color filter formed by an inkjet method is described as an example of the display member.

In the following description, a color filter refers to a filter that causes a display device to perform color display by passing light of a specific wavelength. The color filter is formed by ejecting a liquid material by an ink jet method onto a glass substrate on which black matrix is formed. In addition, black matrix and color filter are formed The glass substrate in this state is called a color filter substrate.

[Embodiment 1]

 FIG. 2 shows an outline of an imaging inspection system 300 that is an inspection apparatus of the present invention.

As shown in FIG. 2, the imaging inspection system 300 inspects the color filter substrate 330 that is an object to be inspected, and irradiates the surface (color filter forming surface) of the color filter substrate 330 with light. An illumination device (irradiation means) 310, a camera (detection means) 320 for imaging reflected light from the color filter substrate 330, and a stage 340 for mounting the color filter substrate 330.

 Note that the camera (detection means) 320 includes an output means for outputting a captured image to the image analysis apparatus (inspection apparatus) 100. The information output from the camera 320 is captured image information including luminance distribution information on the surface of the color filter substrate 330. The luminance distribution information is information indicating a distribution state of luminance values in a predetermined area unit of the color filter substrate 330, for example, a pixel unit.

 The information analyzed by the image analysis device 100 is output to the result output device 400 as unevenness period information described later. Details of the image analysis apparatus 100 will be described later.

[0046] The result output device 400 outputs data that can be confirmed by the operator based on the input unevenness period information, for example, graphed data, as result data. The output result will be described later.

 [0047] The color filter substrate 330 is formed as follows.

FIG. 3 is a diagram showing a part of the manufacturing process (manufacturing method) of the color filter substrate 330 and the discharging process of the liquid material of the color filter by the inkjet method. The head unit 230 moves in the scanning direction (backward or frontward in the drawing) with respect to the glass substrate 220 on which the black matrix 210 is formed, and the ink jet nozzle 240 is liquid on the glass substrate 220 between the black matrix 210. The material is sequentially discharged in the scanning direction. When the ejection in the scanning direction is completed, the head unit 230 moves a predetermined distance in the direction orthogonal to the scanning direction (left and right in the drawing), and then again in the scanning direction (front or back in the drawing). ), The inkjet nozzle 240 sequentially discharges the liquid material in the scanning direction. By repeating the above operation by the head unit 230, a color filter is formed on the color filter substrate 330.

[0049] At this time, when the discharge amount of the liquid material varies for each nozzle 240 of the head unit 230 for some reason, the color filter is unevenly spaced at the nozzle interval.

 [0050] Further, when one nozzle is clogged for some reason, stripes occur in the color filter at intervals of the head unit 230. Specifically, stripes occur in the scanning direction in units of the number of head units 230 arranged in the direction orthogonal to the scanning direction of nozzles 240, for example, in FIG.

 [0051] As described above, when the color filter substrate 330 is formed by the ink jet method, uneven stripes having various periods are generated according to the cause of the color filter substrate 330.

 [0052] Such unevenness is clarified by imaging with the camera 320 which is the imaging means shown in FIG.

 FIG. 4 is a diagram showing an example of an image obtained by imaging the color filter substrate 330 with the camera 320 in a planar (two-dimensional) manner. Here, the stripe unevenness generated when the head unit 230 is used is shown. In the captured image, the direction parallel to the stripe uneven direction is defined as the Y direction, and the direction perpendicular to the stripe uneven direction is defined as the X direction. Yes. Here, the uneven stripe means unevenness recognized as a plurality of stripe-like unevenness on the color filter forming surface of the color filter substrate 330 due to the difference in film thickness. Therefore, the non-uniform direction refers to the longitudinal direction of the formed stripe.

 [0054] In the present invention, the image analysis device 100 that is an inspection device uses the color from the two-dimensional luminance distribution information (light distribution information) extracted from the planar captured image of the color filter substrate 330 that is the object to be inspected. Information for determining the periodicity of stripes occurring in the color filter formed on the surface of the filter substrate 330 is provided.

 FIG. 1 shows a schematic block diagram of an image analysis apparatus 100 that is an inspection apparatus according to the present embodiment.

[0056] As described above, the image analysis apparatus 100 captures image information obtained by the imaging inspection system 300. And a function for outputting to the result output device 400 as uneven period information.

As shown in FIG. 1, the image analysis apparatus 100 includes a one-dimensional projection processing circuit (one-dimensional projection processing means) 110 that converts input two-dimensional luminance distribution information into one-dimensional luminance distribution information, and a primary Periodic analysis processing circuit (periodic analysis processing means) 120 that performs periodic analysis of the one-dimensional luminance distribution information converted by the original projection processing circuit 110, and for sending control signals including various commands to these processing circuits With CPU150.

Specifically, in the image analysis apparatus 100, first, the one-dimensional projection processing circuit 110 acquires captured image information from the imaging inspection system 300 in accordance with an instruction from the CPU 150.

The one-dimensional projection processing circuit 110 converts the two-dimensional luminance distribution information included in the acquired captured image information into one-dimensional luminance distribution information. Details of the one-dimensional projection processing by the one-dimensional projection processing circuit 110 will be described later. Further, according to the instruction of the CPU 150, the one-dimensional projection processing circuit 110 outputs the one-dimensional projection processing result to the periodic analysis processing circuit 120 at the subsequent stage.

 The period analysis processing circuit 120 performs Fourier transform on the input one-dimensional luminance distribution information, and analyzes the periodicity of the one-dimensional luminance distribution information. Details of the period analysis processing by the period analysis processing circuit 120 will be described later. Further, in accordance with an instruction from the CPU 150, the cycle analysis processing circuit 120 outputs the Fourier analysis processing result to the subsequent result output device 400 as uneven cycle information.

 [0061] The result output device 400 outputs the inputted unevenness period information in a form that is easy for a human to recognize, for example, a graph. The operator looks at the output result and determines whether or not the stripes having periodicity are present in the color filter formed on the surface of the color filter substrate 330. Therefore, the result output from the result output device 400 may be in any form as long as it can be determined by the operator.

 [0062] The reflected light from the imaging inspection system 300 is the thickness of the picture element of the color filter substrate 330 where the amount of reflected light is larger in the portion where the thickness of the picture element of the color filter substrate 330 is relatively larger than other regions. However, the amount of reflected light is smaller in a portion where is relatively smaller than other regions. This difference in the amount of reflected light is recognized as unevenness.

[0063] Due to the above-described causes, the difference in film thickness by the ink jet method is generally the head unit. When a large difference in film thickness occurs in one line in the scanning direction of the image 230, stripes are observed in the image data picked up by the camera (detection means) 320.

 [0064] As described above, from the relationship of human visual characteristics, among the uneven stripes generated on the color filter substrate 330, the uneven stripes that occur periodically are conspicuous. Judgment is important for quality improvement.

 Hereinafter, a process for determining the presence or absence of stripe unevenness by the image analysis apparatus 100 having the above configuration will be described.

 First, the one-dimensional projection processing by the one-dimensional projection processing circuit 110 will be described.

 FIG. 4 is a diagram illustrating an example of an image captured by the camera 320 serving as an imaging unit. Note that the one-dimensional projection processing circuit 110 performs one-dimensional projection processing with respect to the light distribution information included in the image data captured by the camera 320 (for example, FIG. 4) with an arbitrary direction as the projection direction. It has become. Here, the projection direction is a direction in which the luminance value is added along the above-described streak direction (direction in which one-dimensional projection processing is performed). In the present embodiment, as shown in FIG. 4, the Y direction parallel to the non-straight direction is taken in the captured image.

 Accordingly, in the one-dimensional projection processing in the present embodiment, the arbitrary value is set as the Y direction, and the luminance value is averaged in the Y direction with respect to the image shown in FIG. One-dimensional distribution information.

 Here, the luminance distribution information of the captured image is represented as p. x

 xy and y are the coordinate values in the X and Y directions, respectively. Using this, the luminance distribution information that is made one-dimensional can be obtained by calculating equation (1).

[0070] Country '... "

[0071] Here, N is the number of data in the Y direction.

FIG. 5 is a graph showing the one-dimensional luminance distribution information obtained by the equation (1). The vertical axis is the luminance value, and the horizontal axis is the position of the X coordinate. The unit of horizontal axis is pixel (pix). [0073] The one-dimensional luminance distribution information obtained in this way is Fourier transformed by the period analysis processing circuit 120 at the subsequent stage.

 [0074] In the present embodiment, as an example of the one-dimensional projection process, a method of taking the average value of the luminance values is used. However, the one-dimensional projection process may be any one that can convert two-dimensional data into one dimension. It is not restricted to this in particular. For example, it may be a method of integrating the luminance value in the Y direction! /, Or a method of adding the weight in the Y direction.

 Next, the cycle analysis process performed by the cycle analysis processing circuit 120 will be described.

 The Fourier transform performed in the period analysis processing circuit 120 is performed using Expression (2).

[0077] [Equation 2]

 [0078] A frequency distribution can be obtained by performing Fourier transform using the above equation (2). Furthermore, if the inverse of the frequency is taken, the result can be a function of the period.

 FIG. 6 is a graph showing the result of Fourier transform of the data one-dimensionally projected by the one-dimensional projection processing circuit 110 (the graph shown in FIG. 5) as it is. The vertical axis shows the intensity of the spectrum. The horizontal axis takes the reciprocal of the frequency, converts it to a period, and displays the logarithm. The unit of the period is a pixel (pix).

 [0080] In this graph, the part A where the remarkable spectrum is observed

 2

 (Spectrum), it can be seen that stripes are generated with periodicity. In this way, by performing Fourier transform, it is possible to obtain data (uneven period information) indicating the presence or absence of periodicity of stripes occurring on the color filter substrate 330.

Here, the irregularity period information is output in the form of a graph or the like that can be recognized by the operator in the result output device 400, so that the operator can determine whether or not the irregularity of the stripes is semi-IJ. ! / Speak.

[0082] It should be noted that, as described above, the determination of the presence or absence of periodic irregularities may be automatically performed based on the relationship between the spectrum and the period included in the unevenness period information that is not obtained by visual judgment by the operator.

[0083] For example, determination of the presence or absence of periodic irregularities, that is, a remarkable spectrum is observed. It is possible to automatically determine whether or not there is a periodicity of streak by reading out the reference information stored in advance and comparing it with the detected spectrum. This criterion information is registered in the criterion database. This criterion database may be provided in the result output device 400 of the imaging inspection system 300 or may be provided separately.

 Specifically, as the determination criterion information, for example, the moving average of FIG. 6 is taken, and the vicinity of the moving average value (for example, a value obtained by multiplying the moving average value by 1.2 is set as the upper limit value and the moving average value is set). The range (with a value multiplied by 8 as the lower limit) is used as the criterion information, and the presence or absence of spectral values that are out of this range! / There is a way to judge. In addition, the presence or absence of the periodicity of stripes may be determined by various other methods.

 [0085] As described above, uneven stripes having various periods occur depending on the cause of occurrence. Therefore, information including the width and period of the uneven stripe predicted in advance is associated with the cause of the uneven stripes. Thus, it may be registered in the determination criterion database, and the cause of the occurrence of streaks may be specified from the width and period of streaks included in the detected unevenness period information and the registered information.

 [0086] For example, as information to be registered in the determination criterion database, a neighborhood value range including a cycle of stripe unevenness associated with the cause of occurrence of stripe unevenness and a range in the vicinity thereof is used. Then, the periodic force included in the unevenness period information is checked in order with respect to the registered period to determine whether it is included in the neighborhood value range of the period registered in the above criteria database. It is determined by whether or not it is included in the neighborhood value range. At this time, if it is determined that the period of the stripe unevenness included in the detected uneven period information is included in the neighborhood value range of the registered period, it is possible to identify the cause of the occurrence of the stripe unevenness of the period. it can.

[0087] Here, the period is set to be expanded to the neighborhood value range because an error may occur due to the positional deviation of the head unit or other causes, and the range is set in consideration of the error. To do. For example, the neighborhood value range is determined from the dimension error value of the mechanism such as the head, the nozzle, and the scanning stage, the operation error value, and the experience value. In addition, to the width of the stripe Information about this may be added to the determination reference database for determination.

As described above, it is possible to feed back the result of the determination to the production process by determining whether or not the stripe has periodicity.

[0089] Further, since a remarkable spectrum is generated in the vicinity of the T pixel, the period of the uneven stripe is T

 2 It can be seen that it is about 2 pixels. In this way, it is also possible to obtain the stripe unevenness period by Fourier transform.

 [0090] As described above, in general, in the inkjet method, stripes with different periods are observed depending on the cause of the occurrence of stripes.

 [0091] Therefore, if it is possible to obtain a further period by simply knowing whether or not the stripe has periodicity, it is possible to know the cause of stripe occurrence and feed it back to the production process.

 [0092] In this case, the determination result may include information for specifying the cause of the occurrence of the uneven stripes in addition to the information indicating the presence or absence of the uneven stripe periodicity.

 Hereinafter, an example in which unevenness period information of the color filter on the color filter substrate 330 is fed back to the production process (manufacturing process) of the color finer substrate 330 will be described.

 In the following description, it is assumed that the step of executing the above-described color filter inspection method (hereinafter referred to as the color filter inspection step) is included in a series of manufacturing steps of the color filter substrate 330. . For example, in the three manufacturing processes (steps S1 to S3) of the color filter substrate shown in FIG. 7, when considering step S2 indicating the color filter inspection process as a reference, step S1 is the previous process and step S3 is The next step.

 As shown in FIG. 7, step S1, which is the preceding process, includes a black matrix manufacturing process and a color filter manufacturing process.

[0096] In the above black matrix manufacturing process, a negative acrylic photosensitive resin liquid in which carbon fine particles are dispersed is applied onto a glass substrate by spin coating, followed by drying! / \ A black photosensitive resin layer is formed. Form. Subsequently, after the black photosensitive resin layer is exposed through a photomask, development is performed to form a black matrix (BM). For example, as shown in FIG. 3, a black matrix 210 is formed on a glass substrate 220. At this time, the opening for use in the color filter manufacturing process, which is the next process, that is, the opening for receiving the ink ejected from each nozzle 240 of the head unit 230 (the color of each color). The black matrix 210 is formed so as to form a filter.

[0097] In the color filter manufacturing process, as described above, the head unit 230 moves in the scanning direction (backward or frontward in the drawing) with respect to the glass substrate 220 on which the black matrix 210 is formed. Inkjet nozzles 240 sequentially eject liquid materials on the glass substrate 220 between the black matrixes 210 in the scanning direction to form color filters on the glass substrate 220. The black matrix 210 may be formed by ink jet or roller transfer. Moreover, you may perform a surface processing process as needed.

[0098] After the previous process of step S1 is completed, a color filter inspection process is executed (step S2). In this color filter inspection process, uneven period information of the color filter is detected, and a non-defective product of the color filter is determined from the detection result.

[0099] Here, in addition to the information indicating the presence / absence of stripe unevenness and the information for identifying the cause of occurrence of stripe unevenness, the uneven cycle information includes the stripe irregularity periodicity information. It is assumed that at least the spectrum in the period is included.

 [0100] For example, in an apparatus that produces a color filter (color filter manufacturing apparatus), the unevenness period information sent from the image analysis apparatus 100, which is the above-described inspection apparatus, includes the fact that the periodicity of stripes exists. If this is the case, the information contained in the irregularity period information is compared with the inspection reference information created and stored in advance, and the color filter processing (processing after the inspection process) is performed according to the comparison result. Change). The inspection standard information may be registered in the above-described determination standard database, or may be registered in another database. If necessary, it can be registered in any database that can be read by the color filter manufacturing apparatus. /!

[0101] Changing the processing of the color filter means, for example, a color value formed with a color finisher determined to be equal to or greater than the first predetermined value included in the spectral power included in the unevenness period information and the inspection standard information. The filter substrate is discarded based on the inspected object processing change information created and stored in advance, and the color filter on which the color filter determined to be less than the first predetermined value and greater than or equal to the second predetermined value is formed. It is conveying a filter board | substrate to a rework process. The color filter substrate on which the color filter determined to be less than the spectral value S included in the unevenness period information and the second predetermined value is determined to be a non-defective product, and the inspection process is performed. Then, it is conveyed to the next manufacturing process to be executed.

[0102] The color filter transported to the above-mentioned rework process is a color filter that is determined to be in a repairable state, and is reworked together with rework information including location information of abnormal points obtained in the color filter inspection process. After being transported to the process and repaired in this rework process, it is transported again to the inspection process and inspected. The reworking process is included in the black matrix manufacturing process and the color filter manufacturing process in step S1 of the power filter substrate manufacturing process. In the rework process, there are cases of local repair that repairs only abnormal parts and full repair of the color filter substrate, repair of only the color filter, and repair of the black matrix and color filter. There are cases.

 [0103] In addition, in the color filter inspection process in step S2, the spectrum value and the like when it is determined that the disposal process is performed is fed back to the previous process S1. When fed back to the color filter manufacturing process, the color filter manufacturing process changes the manufacturing conditions in the color filter manufacturing process (for example, adjustment of ink ejection amount, head Change the moving speed of the unit, etc.) and manufacture the color filter. Furthermore, if it is determined in the color filter inspection process in step S2 that unevenness due to the inappropriate width of the black matrix has occurred, the black matrix manufacturing process is compared with the black matrix manufacturing process. Instruct the condition change (adjustment of photomask formation position to form black matrix, etc.). In the black matrix manufacturing process, the manufacturing conditions are changed according to the instructed contents, and the black matrix is manufactured. The decision to change the manufacturing conditions based on the spectrum value and the judgment reference database may be made on the pre-manufacturing process side, or on the color filter inspection process side, and an instruction to change the manufacturing conditions is sent to the pre-manufacturing process. May be sent.

[0104] The color filter substrate on which the color filter determined to be non-defective after the inspection is completed as described above is transported to the next step (step S3). Even if it is determined that the product is non-defective, if it is close to the limit value of the non-defective product, the manufacturing conditions are set so that the next process is executed under the manufacturing conditions that consider the color filter inspection results. Change instructions Good.

 [0105] In step S3, a counter electrode made of a transparent electrode such as ITO is formed by sputtering, and then a columnar spacer (not shown) for defining the cell gap of the liquid crystal panel, for example, is an acrylic photosensitive resin. It is formed by applying a resin solution and exposing, developing and curing with a photomask.

 [0106] The color filter substrate 330 is formed as described above.

 [0107] As described above, since the color filter after the inspection can be processed according to the inspection result based on the unevenness period information that is the inspection result obtained in the color filter inspection process, it is finally obtained. The yield of good color filters can be improved.

 [0108] Moreover, even if there is periodicity of stripes, it is determined whether or not it can be repaired by the degree of occurrence of stripes (the magnitude of the spectrum value). All the color filters that have undergone non-defective product are not defective. Will be discarded as a defective product. As a result, wasteful disposal of the color filter can be eliminated, and the power S can be improved by improving the yield of the color filter and reducing the manufacturing cost.

 [0109] Thereby, the power and time required for manufacturing the color filter can be reduced in total.

[0110] The processing change of the color filter that is the work to be inspected may be made for a single color filter, for all the color filters of the lot to which it belongs, or for a power color filter of the same model number. You may go to all.

 [0111] For a color filter that is determined to be a defective product, a marking or the like may be provided at a predetermined predetermined position of the color filter substrate or an abnormality occurrence region of the color filter.

 [0112] In this case, the color filter determined to be a defective product is not discarded in the manufacturing process and is used by the operator to identify the cause of the defective product.

[0113] In addition, inspection values obtained in the inspection process of a plurality of color filters (or a plurality of locations in the color filter) are stored in an inspection value database (for example, installed in an inspection apparatus). The manufacturing process and the manufacturing process conditions described may be changed when the conditions applicable to the conditions described in the inspection standard information registered in the judgment standard database are met.

 [0114] For example, the number of consecutive color filters whose frequency value is greater than or equal to a certain reference value (the first predetermined value or the second predetermined value described above) or the frequency of occurrence is counted. If the specified frequency is exceeded, the manufacturing process is changed based on the inspection result. Based on the manufacturing process change information, the manufacturing method is changed by feeding back to the manufacturing process before the process causing the failure. .

 [0115] Examples of changes in the manufacturing method include changing the manufacturing conditions of the manufacturing apparatus, starting a check inspection for the necessity of maintenance of the manufacturing apparatus, stopping the manufacturing apparatus, It is conceivable to perform cleaning or replacement of the parts.

 [0116] In addition, the manufacturing method may be changed by transmitting the inspection value to a manufacturing process after the inspection process.

 [0117] For example, for a color filter in a lot that belongs to a predetermined number or more of the inspection value (spectrum value) that exceeds a certain standard, the manufacturing condition of the next manufacturing process is reduced, and the high inspection value is relaxed For example, it may be changed according to the manufacturing process change information so that the final luminance value falls within the range of the final inspection standard.

[0118] In the present embodiment, as an example of the periodic analysis process, the force periodic analysis process using the Fourier transform for the periodic analysis process is particularly suitable if it can check the presence of periodicity. Not limited! /.

[0119] In the present embodiment, the surface of the display member is irradiated with light and the analysis is performed based on the reflected light distribution. However, the analysis may be performed based on the transmitted light distribution.

[0120] Even when the transmitted light distribution is used, the image processing procedure is the same as the image processing procedure using the reflected light distribution.

[0121] For example, the periodic analysis described above may be performed based on the transmitted light distribution obtained by irradiating the back surface of the display member (color filter) with light and transmitting the light to the front surface that is the color filter formation surface. Conceivable.

[0122] In this case, the lighting device is arranged on the color filter non-formation side (the back side of the display member), and the camera is Is placed on the color filter forming side (front side of the display member). It is desirable to set the camera arrangement angle to an angle at which unevenness appears easily on the color filter forming surface. For example, as in the case of reflection, it is desirable that the irradiation angle with respect to the back surface of the substrate and the emission angle of the transmitted light with respect to the substrate are different from those of the straight transmitted light. Specifically, the illumination device is arranged in the normal direction of the substrate and the camera is arranged at an angle inclined from the normal line of the substrate, or the illumination device is arranged at an angle inclined from the normal line of the substrate. It is conceivable to arrange them at an angle inclined from the normal direction of the substrate and the direction of the straight transmitted light.

In the first embodiment, filtering processing (morphology processing) may be performed on the data subjected to the one-dimensional projection processing before performing force cycle analysis processing in which cycle analysis processing is performed as it is.

 [0124] Note that the filtering process in this specification refers to a process of extracting or suppressing irregularities having a certain periodic width with respect to information obtained by one-dimensional projection of light distribution information (luminance distribution information).

 [0125] In the following Embodiment 2, the case where the morphology process is used as an example of the filtering process will be described. In Embodiment 3, the case where the smoothing process is used as an example of the filtering process will be described. Further, in the fourth embodiment, a case where both morphology processing and smoothing processing are used will be described.

 [Embodiment 2]

 Another embodiment of the present invention will be described as follows. In the present embodiment, the same processing circuit as that described in the first embodiment is given the same name and the same member number, and the description thereof is omitted.

 FIG. 8 shows a schematic block diagram of the image analysis apparatus 102 that is effective in the present embodiment. Here, the difference from the image analysis apparatus 100 shown in FIG. 1 of the first embodiment is that a morphology processing circuit 130 is provided after the one-dimensional projection processing circuit 110.

 That is, in the image analysis device 102, the one-dimensional projection processing circuit 110 performs one-dimensional projection processing on the one-dimensional luminance distribution information, the morphology processing circuit 130 performs filtering, and then the periodic analysis processing circuit 120 performs the filtering process. Periodic analysis processing is performed.

It should be noted that the morphology processing circuit 130 is also controlled by a control signal from the CPU 150 in the same manner as other processing circuits. Here, the morphology processing in the morphology processing circuit 130 will be described.

[0131] FIGS. 9A and 9B are schematic diagrams for explaining the morphology processing used in the present embodiment.

 There are two types of morphology processing in the present embodiment: black morphology processing and white morphology processing.

 [0133] Black morphology processing is processing that suppresses recesses that are larger than a certain width (filter size) (straightness that is lower than the surrounding luminance), and white morphology processing is a certain width (filter size). ) This is a process that suppresses convex parts with a larger width (higher brightness values than the surrounding brightness! /, Uneven stripes).

 [0134] Black morphology processing is performed to maximize the luminance value in the filtering area while scanning in the X direction for the one-dimensional data (shown by the solid line in Fig. 9 (a)). Processing is performed to obtain a maximum value distribution (indicated by a broken line in Fig. 9 (a)), and the minimum value for obtaining the minimum value of the luminance value in the filtering region while scanning the maximum value distribution in the X direction. After processing, the minimum value distribution (shown in bold in Fig. 9 (a)) is obtained, the difference between the one-dimensional data and the minimum value distribution is obtained, and the morphology distribution (shown in solid line in Fig. 9 (b)). This is the process for obtaining

 Specifically, it can be obtained by solving the following equation (3). Here, f is a constant input to determine the filter size, and 2f + 1 is the filter size.

[0136] [Equation 3]

 [0137] However, Min [] and Max [] in Equation (3) are operators represented by the following Equations (4) and (5). Minf [] is an operator that selects the minimum value of the sequence in [], and Maxf [] is an operator that selects the maximum value of the sequence in [].

[0138] 圖

[0139] [Number 5

[0140] As a result of black morphology processing, the concave portion with a width smaller than the filter size (2f + l) is extracted. It becomes possible.

 [0141] The white morphology processing is the reverse of the black morphology processing and is expressed by the following equation (6). in this case

It is possible to extract a convex portion smaller than the filter size (2f + l).

[0142] [Equation 6]

 FIG. 10 is a flowchart showing the flow of processing of the inspection method in the present embodiment. In this flowchart, the processing in the one-dimensional projection processing circuit 110 is omitted, and the processing flow in the morphology processing circuit 130 and the period analysis processing circuit 120 is shown. In addition, the following procedures are performed for white morphology processing and black morphology processing, respectively.

Five.

 First, N = l is set (step S l). Here, N is a specific integer.

 Next, with f = 2N, it is determined whether 2f + 1 is smaller than MAX (step S2). Here, MAX is a specific integer such as 128, 256, 512, or 1024.

[0146] In step S2, if 2f + l is smaller than MAX, the filter size is set to 2f + 1, and the morphology processing is performed on the luminance distribution information subjected to the one-dimensional projection processing (step S3

).

 [0147] Further, Fourier transformation is performed on the result of the morphology processing (step S4).

[0148] Subsequently, the result obtained by the Fourier transform is output to the result output device 400 (step S5).

 [0149] Finally, N = N + 1 is set, and the process returns to step S2 (step S6).

 [0150] Steps S3 to S6 are repeated until it is determined that 2f + l indicating the filter size is greater than or equal to MAX. That is, when it is determined that 2f + 1 is greater than or equal to MAX, the process of the flowchart shown in FIG. 10 ends.

 [0151] By comparing the obtained results in this way, it becomes easier to inspect the stripe unevenness period. This will be described below.

 [0152] Here, the result when the filter size in the white morphology processing is f pixels, and f

 The results for a larger f pixel are described below.

 1 2

[0153] Figure 11 shows the result of morphology processing with the filter size set to fl pixels. It is rough. Note that the vertical axis is contrast, the horizontal axis is the X coordinate position as in the graph of the one-dimensional projection processing result, and the unit is pixel (pix).

 [0154] FIG. 12 is a graph showing a result when Fourier transform is further performed from the result of performing the morphology processing shown in FIG. Here, like the Fourier transform result shown in the first embodiment, the vertical axis indicates the intensity of the spectrum. The horizontal axis takes the reciprocal of the frequency, converts it to a period, and displays the logarithm. The unit of period is pixel (pix).

 [0155] From the graph shown in Fig. 12, as a result of the suppression of stripe unevenness with a width larger than the filter size fl by morphology processing, the spectrum B due to the stripe unevenness with a period of T1 pixels (relatively small! /, Stripe unevenness) is particularly It can be seen that the output is emphasized.

 In the graph shown in FIG. 12, the spectrum is also observed around pixel B having a period smaller than the T pixel. This is due to the width of the T pixel as a result of the Fourier transform. A harmonic of period T appears, indicating that it contributes to the accuracy of determining the existence of the spectrum of the fundamental period! /.

 [0157] By performing the morphology processing in this way, it becomes easy to inspect the period of unevenness occurring with a specific period.

 [0158] Figure 13 shows the results of morphology processing with the filter size set to f pixels.

 2

 It is shown similarly.

FIG. 14 shows the result when Fourier transform is performed as in FIG.

[0160] From the graph shown in Fig. 14, it is clear that the period with T pixel A is particularly emphasized.

 2

 Power.

 [0161] In the graph shown in Fig. 14, the period is around T / 2 pixenore Al and T / 3 pixenore A2.

 twenty two

 Also the spectrum observing force s, which is due to the width of τ pixel as a result of Fourier transform

 2

 As a result, the harmonics of period τ appear, and the reliability of determining the existence of the spectrum of the fundamental period

 2

 Show that it contributes!

[0162] In this way, by comparing the processing results, the non-uniformity with a period of T pixels and the period with a T pitch.

 2 1 Kussell's smoothness and strength S.

[0163] In the first embodiment, the period analysis is performed on the data subjected to the one-dimensional projection processing as it is. However, as shown in Fig. 6, when a large number of stripes with different periods are mixed. If one-dimensional projection data is Fourier-analyzed as it is, it is observed in a state where a plurality of spectra are mixed due to a plurality of stripe irregularities having different periods.

 [0164] However, by performing the morphology process before performing the Fourier transform as in the present embodiment, in the Fourier transform, when stripes having a plurality of widths occur in different periods, a specific width Since only the spectrum due to the uneven stripes is emphasized and observed, the period of uneven stripes can be easily inspected.

 [0165] Furthermore, as described above, by changing the filter size of the morphology process and repeating the morphology process and the Fourier transform, various periods can be extracted according to the process size of the morphology process, and a specific period can be extracted. This makes it easier to inspect the spectrum of a striped stripe.

 [Embodiment 3]

 Another embodiment of the present invention will be described as follows. In the present embodiment, the same processing circuit as that described in the first embodiment is given the same name and the same member number, and the description thereof is omitted.

 FIG. 15 shows a schematic block diagram of the image analysis apparatus 103 that is effective in the present embodiment. Here, the difference from the image analysis apparatus 100 shown in FIG. 1 of the first embodiment is that a smoothing processing circuit 140 is provided after the one-dimensional projection processing circuit 110.

 That is, in the image analysis apparatus 103, the one-dimensional projection distribution circuit 110 performs one-dimensional projection processing on the one-dimensional luminance distribution information filtered by the smoothing processing circuit 140, and then performed by the periodic analysis processing circuit 120. Periodic analysis processing is performed.

 Note that the smoothing processing circuit 140 is also controlled by a control signal from the CPU 150, as in the case of other processing circuits.

 [0170] Here, the smoothing processing in the smoothing processing circuit 140 will be described.

 [0171] The smoothing process is a process of obtaining an average value distribution by performing an averaging process for obtaining an average value in a predetermined region while scanning in the X direction with respect to the one-dimensional data.

 [0172] Specifically, it can be obtained by solving the following equation (7).

 [0173] [Equation 7]

H, = Av _f [P _x ] (7)

[0174] Here, AV [] is expressed by the following equation (8). AV [] selects the average value of the sequence in [] Operator.

[0175] [Equation 8] = one, ... '", /} · · · · (8)

[0176] However, as in the case of morphology processing, f is a constant input to determine the filter size, and 2f + l is the filter size.

[0177] The smoothing process suppresses uneven stripes having a width equal to or smaller than the filter size (2f + l), so that the period of uneven stripes can be easily obtained.

[0178] Figure 16 shows the filter size force pixel plane for the one-dimensional projection result shown in Figure 5.

 Three

 The result of having performed the smoothing process is shown. The vertical axis is the luminance value, the horizontal axis is the position of the X coordinate as in the one-dimensional projection processing result graph, and the unit is pixel (pix).

[0179] This suppresses stripes with stripe width less than f pixels, and f pixels or more.

 3 3

 This makes it easier to inspect the period of stripes with a width of.

Further, FIG. 17 shows the result of Fourier transform performed on the smoothing processing result by the period analysis processing circuit 120. The vertical axis indicates the intensity of the spectrum. The horizontal axis takes the reciprocal of the frequency, converts it to a period, and displays the logarithm. The unit of period is pixel (pix).

 [0181] Compared to Fig. 6 of the first embodiment, it can be seen that Fig. 17 suppresses the spattering due to the uneven stripe having a period of T1 pixel that was observed in Fig. 6.

[0182] In this way, when the filter size force ¾ pixel is smoothed, f pixels (

 3 3

 It is possible to suppress the spectrum due to the stripe unevenness generated with a width smaller than (Pix), and to easily inspect the period of unevenness.

 [0183] Also in this case, as in the second embodiment, the smoothing process and the Fourier transform are repeated by changing the smoothing process filter size, and according to the smoothing process filter size, Various periods can be extracted, making it easier to examine the spectrum of stripes with a specific period.

[0184] In the present embodiment, as an example of the smoothing process, a method of simply obtaining an average value is used. However, this is particularly applicable to a process that suppresses uneven stripes having a width smaller than a certain width. It is not limited. For example, smoothing may be performed using local weights, or a method of drawing an approximate curve using a polynomial.

[Embodiment 4]

 Another embodiment of the present invention will be described as follows. In the present embodiment, the same processing circuit as the processing circuit described in the above embodiments;! To 3 is given the same name and the same member number, and the description thereof is omitted.

FIG. 18 shows a schematic block diagram of the image analysis device 104 that is effective in the present embodiment. Here, the difference from the image analysis apparatus 100 shown in FIG. 1 of the first embodiment is that a morphology processing circuit 130 and a smoothing processing circuit 140 are provided after the one-dimensional projection processing circuit 110. It is a point.

 That is, in the image analysis device 104, the one-dimensional luminance distribution information subjected to the one-dimensional projection processing by the one-dimensional projection processing circuit 110 is filtered by the morphology processing circuit 130 and the smoothing processing circuit 140, and then subjected to periodic analysis. A period analysis process is performed by the processing circuit 120.

 It should be noted that the morphology processing circuit 130 and the smoothing processing circuit 140 are also controlled by a control signal from the CPU 150 in the same manner as other processing circuits.

 [0189] As described above, in this embodiment, by performing both the filtering processing (morphology processing and smoothing processing) performed in Embodiment 2 and Embodiment 3, respectively, the smoothing of the stripes can be further accurately performed. Periodicity and its period can be determined.

 In the present embodiment, a case will be described in which, after smoothing processing by the smoothing processing circuit 140, morphology processing by the morphology processing circuit 130 is performed on the smoothing processing result.

FIG. 19 shows the result of the morphology processing shown in the second embodiment on the data that has been subjected to the smoothing processing described above (the data shown in the graph of FIG. 16 in the third embodiment). It is a thing. Note that the vertical axis is contrast, the horizontal axis is the position of the X coordinate as in the graph of the one-dimensional projection processing result, and the unit is pixel (pix).

Furthermore, FIG. 20 shows the result of the Fourier transform performed by the period analysis processing circuit 120 on the morphology processing result. The vertical axis indicates the intensity of the spectrum. The horizontal axis is the frequency The reciprocal is taken, converted into a period, and displayed logarithmically. The unit of period is pixel (pix).

 [0193] Comparing the graph shown in FIG. 20 with the graph shown in FIG. 15, the graph shown in FIG. 20 emphasizes the spectrum due to the stripe unevenness near the T2 pixel. This is thought to be due to the fact that the smoothing process suppressed the spectrum due to stripes that were smaller than the filter size! This is a peculiar effect by combining smoothing processing and morphology processing, and this makes it possible to obtain the stripe unevenness period more accurately.

 [0194] Further, when the graph shown in FIG. 20 is compared with the graph shown in FIG. 15, the spectrum due to the streaks in the vicinity of the forces S and T1 of the graph shown in FIG. 20 is suppressed. This is thought to be due to the effect of suppressing the spectrum due to stripe unevenness that occurs with a width smaller than the filtering size (f3 pixel (Pix)) by the smoothing process. As a result, the stripe unevenness period can be obtained with higher accuracy.

 Thus, by performing both the morphology process and the smoothing process, it becomes easier to inspect the period of unevenness.

 [0196] In the present embodiment, as in the second and third embodiments, the smoothing process, the morphology process, and the Fourier transform are performed by changing the filter sizes of the smoothing process and the morphology process. By repeating, it is possible to extract various periods according to the filter size, and it becomes easy to inspect the spectrum of stripes having a specific period.

 [0197] As described above, in the first to fourth embodiments, as an example of the filtering process, the information on the one-dimensional projection of the intensity distribution information using the morphology process and the smoothing process is used. Thus, the process is not particularly limited as long as it is a process for extracting or suppressing irregularities having a certain period width.

 [0198] Further, in Embodiments 1 to 4, force using a color filter created by an inkjet method as an object to be inspected is not limited to this, and color filters created by other production methods In this case, the present invention can be implemented.

[0199] For example, in the case of a pigment dispersion method in which photolithography is performed for each color, a pixel with a defective color may become uneven, or the surface of the color filter may be scratched for some reason. In some cases, the present invention can be implemented.

[0200] Further, in each of the above-described embodiments, if the unevenness that appears on the one-dimensional projection data is the force S that has been detected with respect to the unevenness in the color filter, the unevenness is not necessarily a streak-like unevenness. The present invention can be implemented.

[0201] In each of the above embodiments, a color filter is used as an object to be inspected. However, if the display member is used in an image display device and transmits or reflects light or both, For example, a surface glass or a rear glass used for a display may be used as an object to be inspected, and a diffusion plate in a knock light unit may be used as an object to be inspected. It can also be applied to inspection of reflectors and screens that project images.

[0202] The present invention is not limited to the above-described embodiments, and various modifications are possible within the scope of the claims.

[0203] Finally, each block of the image analysis devices 100 to 103, in particular, the one-dimensional projection processing circuit 110, the periodic analysis processing circuit 120, the morphology processing circuit 130, and the smoothing processing circuit 140 are configured by hardware logic. Alternatively, it may be realized by software using a CPU as follows.

 That is, the image analysis apparatus 100 includes a CPU (central processing unit) that executes instructions of a control program that implements each function, a ROM (read only memory) that stores the program, and a RAM ( random access memory), and a storage device (recording medium) such as a memory for storing the above program and various data. An object of the present invention is a recording medium in which a program code (execution format program, intermediate code program, source program) of a control program of the image analysis apparatus 100, which is software that realizes the above-described functions, is recorded so as to be readable by a computer. This can also be achieved by supplying the above to the image analysis apparatus 100, and the computer or CPU or MPU) reads out and executes the program code recorded on the recording medium.

[0205] Examples of the recording medium include a tape system such as a magnetic tape and a cassette tape, a magnetic disk such as a floppy (registered trademark) disk / hard disk, and a CD-ROM / MO / MD / DVD / CD-R. Disc system including optical disc, IC card (including memory card) /) Card systems such as optical cards, or semiconductor memory systems such as mask ROM / EPROM / EEPROM / flash ROM can be used.

[0206] The image analysis apparatus 100 may be configured to be connectable to a communication network, and the program code may be supplied via the communication network. The communication network is not particularly limited. For example, the Internet, intranet, extranet, LAN, ISDN, VAN, CATV communication network, virtual private network, telephone line network, mobile communication network, satellite communication A net or the like is available. Also, the transmission medium constituting the communication network is not particularly limited. For example, IEEE1394, USB, power line carrier, cable TV line, telephone line, ADSL line, etc. ooth (registered trademark), 802.11 wireless, HDR, mobile phone network, satellite line, terrestrial digital network, etc. can also be used. The present invention can also be realized in the form of a computer data signal embedded in a carrier wave, in which the program code is embodied by electronic transmission.

 Industrial applicability

[0207] The present invention can be applied to any member as long as the periodicity of unevenness generated on a surface that can transmit or reflect light is a problem. Is possible.

Claims

The scope of the claims

 [1] An inspection apparatus for inspecting a display member based on captured image data obtained by imaging a light-exposed inspection plane of the display member! /,

 One-dimensional projection processing means for performing one-dimensional projection processing with an arbitrary direction as a projection direction for the light distribution information included in the captured image data;

 An inspection apparatus comprising: periodic analysis processing means for performing periodic analysis of light distribution information subjected to one-dimensional projection processing by the one-dimensional projection processing means.

[2] The inspection apparatus according to [1], wherein the period analysis processing means performs Fourier transform on the light distribution information.

[3] It comprises filtering processing means for performing filtering processing on the light distribution information subjected to the one-dimensional projection processing by the one-dimensional projection processing means using a filter of an arbitrary size, and the periodic analysis processing means includes the filtering processing means. The detection device according to claim 1 or 2, wherein periodic analysis of the filtered light distribution information is performed.

 [4] The inspection apparatus according to [3], wherein the filtering processing in the filtering processing means is morphology processing.

5. The inspection apparatus according to claim 3, wherein the filtering process in the filtering process means is a smoothing process.

[6] The filtering processing means includes:

 A smoothing processing circuit for performing smoothing processing on the light distribution information subjected to the one-dimensional projection processing by the one-dimensional projection processing means;

 A morphology processing circuit for performing morphology processing on the light distribution information smoothed by the smoothing processing circuit,

 4. The inspection apparatus according to claim 3, wherein the light distribution information subjected to the morphology processing by the morphology processing circuit is output to the periodic analysis processing means.

[7] The filtering processing means includes:

A morphology processing circuit for performing morphology processing on the light distribution information subjected to the one-dimensional projection processing by the one-dimensional projection processing means; A smoothing processing circuit for performing a smoothing process on the light distribution information subjected to the morphology processing by the morphology processing circuit,

 4. The inspection apparatus according to claim 3, wherein the light distribution information smoothed by the smoothing processing circuit is output to the period analysis processing means.

[8] The inspection device according to any one of [1] to [7], wherein the display member is a color filter.

[9] an illuminating device for irradiating light onto the inspection symmetry plane of the display member;

 An imaging device for imaging the inspection target surface of the display member in a state where light is irradiated by the illumination device;

 An imaging inspection system comprising: the inspection device according to any one of claims 8 to 8, wherein the display member is inspected based on captured image data captured by the imaging device.

 [10] An inspection method for inspecting the display member based on imaged image data obtained by imaging the inspection symmetry plane irradiated with light on the display member! /

 A first step of performing one-dimensional projection processing with an arbitrary direction as a projection direction for the light distribution information included in the captured image data;

 And a second step of performing periodic analysis of the light distribution information after the one-dimensional projection processing obtained by the first step.

[11] Between the first step and the second step,

 There is provided a filtering processing step for filtering the light distribution information after the one-dimensional projection processing obtained in the first step using a filter of an arbitrary size, and the second step includes

 11. The inspection method according to claim 10, wherein a periodic analysis of the light distribution information after the filtering process obtained by the filtering process step is performed.

[12] A color filter manufacturing method for manufacturing a color filter by a color filter manufacturing apparatus,

An inspection process for executing the inspection method according to claim 10 or claim 11 is included. See

 A method for producing a color filter, wherein only the color filter determined to be a non-defective product as a result of the periodic analysis in the inspection method process is used in the manufacturing process after the inspection process in the color filter manufacturing apparatus. .

[13] A color filter manufacturing method for manufacturing a color filter by a color filter manufacturing apparatus,

 Including an inspection process for executing the inspection method according to claim 10 or claim 11,

 When a color filter determined to be defective as a result of periodic analysis by the inspection process occurs, information indicating that a defective product has occurred is transmitted to the color filter manufacturing apparatus. Manufacturing method.

[14] An inspection program for causing a computer to function as each means of the inspection apparatus according to any one of claims;! To 8.

[15] A computer-readable recording medium on which the inspection program according to claim 14 is recorded.