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CN1937698A - Image processing method for image distortion automatic correction - Google Patents

Image processing method for image distortion automatic correction Download PDF

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Publication number
CN1937698A
CN1937698A CN 200610117277 CN200610117277A CN1937698A CN 1937698 A CN1937698 A CN 1937698A CN 200610117277 CN200610117277 CN 200610117277 CN 200610117277 A CN200610117277 A CN 200610117277A CN 1937698 A CN1937698 A CN 1937698A
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赵群飞
张森
孙明
森泽太平
赖尾修三
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Shanghai Jiaotong University
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Abstract

A image processor of automatic calibrating aberration makes use of radon transforming to pick up four sides profiles of business cards and texts, with profile vertex message, we can calibrate the image aberration and establish internal mathematics module of shot equipment and equation groups of business cards and texts aspect ratio parameter, then solve equation groups to get the rectangle object's aspect ratio and apply it to calibrate images to prevent distortion. At last, the invention can identify the image inversion by words identification for judging if it is necessary to circumvolve the calibrated images to get the perfect calibration results. It is very easy to calibrate images without manual practice , we can utilize the invention in most of the imaging equipments ,such as medical imaging, supervising equipment, mobile, digital camera ,digital vision and so on, no wonder that every user can do the operation very easily.

Description

Picture distortion is from the image processing method of dynamic(al) correction
Technical field
What the present invention relates to is a kind of method of technical field of image processing, specifically is the image processing method of a kind of picture distortion from dynamic(al) correction.
Background technology
When taking data such as business card, text with capture apparatus such as digital camera or mobile phones, the image that was photographed tends to tilt, and the object of original rectangles such as business card, text can take place to distort and become arbitrary quadrilateral.Its reason is when taking business card or text, photographer not over against and perpendicular to subject, but certain horizontal range and deviation angle are arranged apart from subject.And photographer is when taking these data, seldom can go over against and vertical, therefore, this distortion phenomenon is very common, to people read these above data information or cause some difficulties when carrying out word processing.
Find by prior art documents, Chinese patent publication number: CN1607824A, open day is on April 20th, 2005, denomination of invention: image processing system and image processing method and electronic camera and image processing apparatus.A cover image processing system and a processing method thereof described in this invention, and its image processing system is made up of Electrofax and image processing apparatus.Wherein, Electrofax comprises image pickup part, the image recording portion, machining information obtaining section and processed record information portion, image pickup part is taken the body that is taken, the image that image recording portion record is photographed by this image pickup part, and the machining information obtaining section is according to the image that is recorded in this image recording portion, obtain the machining information that uses in the regulation processing to this image, processed record information portion will be by this obtaining section machining information of obtaining and the image corresponding record that obtains the source.Image processing apparatus, it possesses taken the image of record by Electrofax, by the machining information of described Electrofax record, carries out the image processing part that regulation is processed according to answering with this image degree.In this invention, the image that Electrofax photographs is presented on the monitor with regeneration mode, if the user needs the correction image distortion, the user need do it yourself to operate the tetragonal outline line that becomes benchmark when identification is revised so, after finding the outline line of wanting, determine operation, the coordinate information on 4 summits of the outline line selected is write the title portion of the image file of display image.Afterwards, when revising, image processing apparatus therefrom reads coordinate information and carries out the correction operation.This technological invention needs the user to do it yourself to operate, and can not realize that from dynamic(al) correction, process complexity, accuracy are not high, except digital camera, also needs personal computer (PC) and projecting apparatus, the equipment complexity, and processing procedure is slower.
In addition, Photoshop software (software towards Digital Image Processing of U.S. Adobe company exploitation) also can be realized the function of image distortion correction, but must on personal computer, implement, need the user to start to regulate and proofread and correct angle, therefore in the operating process error can appear, accuracy is not high, can not realize zero offset capability.And this software can only proofread and correct the trapezoidal distortion of buildings such as building, and the shape that can not proofread and correct business card, text tilts and the distortion of platform shape, and range of application is little.
Summary of the invention
The present invention is directed to the deficiencies in the prior art, the image processing method of a kind of picture distortion from dynamic(al) correction is provided.The shape that the present invention can proofread and correct business card, text tilts and the distortion of platform shape, can realize distortion correction fast, and whole process does not need artificial participation, really realizes from dynamic(al) correction, is easy to realize, and is simple to operate.
The present invention is achieved by the following technical solutions, comprises five steps:
(1) extracts profile: utilize otsu algorithm (big Tianjin algorithm) to carry out automatic threshold and cut apart, adopt morphological method to carry out edge contour and extract;
(2) resolve profile: utilize radon conversion (a kind of projective transformation that is used for straight-line detection that Austrian mathematician Radon proposes) will go up edge contour that the step extracts and separate out, and try to achieve the coordinate of four end points with the formal solution of linear equation;
(3) calculate aspect ratio: be created as the Mathematical Modeling of picture device interior optical imagery, utilize optical imagery knowledge, set up equation group, try to achieve aspect ratio;
(4) distortion correction: utilize two groups of coordinates to try to achieve the distortion correction matrix image is proofreaied and correct, the aspect ratio of image remains unchanged in the trimming process;
(5) rectification building-out: in the time of digital above the method for utilizing digit recognition is judged the image after proofreading and correct inverted phenomenon takes place, select whether need image rotating, the image of finishing after the correction can not proofreaied and correct.
Among the present invention, at first extract tetragonal edge contours such as business card, text, four edges is separated.Wherein, profile extracts used big Tianjin algorithm, is the fast method that a kind of automatic threshold is cut apart.This method can calculate the segmentation threshold of cromogram or gray-scale map very soon, and converts former figure to binary map.Among the present invention, utilize business card, text etc. and the difference of background on brightness and colorfulness, big Tianjin algorithm is cut apart when converting binary map in threshold value background is made as black automatically, and business card etc. are made as white, therefore, in the binary map that obtains, comprise two parts: the business card or the text of the background of black and white.When morphology extracts the border, utilize the Boundary Extraction operator that binary map is carried out computing, edge contour can be extracted, like this, obtain a tetragonal binary map of white.
When resolving profile, the radon conversion of using is a kind of algorithm of straight-line detection.The white tetragonal binary map that step (1) obtains is used the radon conversion, obtain the radon conversion figure of four corresponding bright spots.The corresponding tetragonal limit of each bright spot by reading the XY coordinate figure of the correspondence of bright spot on radon conversion figure, can be obtained the straight line analytic expression on every limit come.Tetragonal four end points coordinates can be obtained in per two limits of simultaneous.
Imaging device internal imaging process is followed lens image formation rule.Suppose that rectangle thing length and width such as business card or text are respectively l, m, with respect to photographer's rectangle anglec of rotation is α, take the lens primary optical axis and the camera plane angle theta of equipment, the coordinate of rectangular centre in the rectangular coordinate system at shooting area place is (x0, y0), the shooting area center is D to the optical center of lens distance, optical coefficient is k, one has 8 unknown parameters, can four end points coordinate representations of rectangle be come out with these 8 parameters, utilize two special light then: the light of crossing the light of primary optical axis and being parallel to primary optical axis is obtained the coordinate of four end points on imaging screen come.Like this, utilize tetragonal four end points coordinates of trying to achieve in the step (2) again, can form an equation group by simultaneous, comprise 8 equations and 8 unknown numbers,, can solve the length-width ratio of rectangle, just aspect ratio by the group of solving an equation.
Carry out timing, need to proofread and correct the coordinate of preceding four end points, i.e. the coordinate of being tried to achieve in the step (2), and the coordinate of proofreading and correct back four end points.Can be with the coordinate before proofreading and correct, and after proofreading and correct quadrangle become the condition of rectangle and proofread and correct after keep the condition of the aspect ratio of trying to achieve, obtain the coordinate of proofreading and correct back four end points.Utilizing these two groups of coordinates to try to achieve the distortion correction matrix proofreaies and correct.
Trimming process becomes rectangle with the quadrangle of distortion on the one hand, also will keep aspect ratio constant on the other hand.But after the correction, business card or the Word message above the text be it seems for the reader, may be inverted.Therefore, need utilize the technology of literal identification, whether numeral or the English alphabet differentiated above the business card are inverted.If inverted, image rotating is judged again so, to guarantee that literal is not put upside down among the last result.
The present invention can be used as the central processing module that the distortion correction submodule embeds imaging device inside, makes imaging device have the automatic distortion correction function.The distortion correction submodule is shared identical digital signal processing chip with central processing module on hardware, use digital image processing method of the present invention on the software, realizes automatic distortion correction on function.
Compared with prior art, the present invention can realize distortion correction fast, and whole process does not need artificial participation, really realizes from dynamic(al) correction.And, introduce the optical imagery Mathematical Modeling, try to achieve the former aspect ratio of business card, text, make and proofread and correct the result and keep original aspect ratio constant, guarantee that last correction result is undistorted in shape.At last, use literal identification, determine the not inversion of business card, the Word message above the text, use simple and convenient.The present invention can be used in most of imaging devices such as medical imaging, watch-dog, mobile phone, digital camera, Digital Video, and need not do big change on hardware, realizes simple.
Description of drawings
Fig. 1 is the inventive method flow chart
Fig. 2 is an imaging device internal optics imaging Mathematical Modeling.
Fig. 3 is the plane graph of shooting area.
Embodiment
The present invention utilizes the radon conversion to extract four cincture exterior features of business card, text fast, utilize the profile vertex information, fault image is proofreaied and correct, and, set up capture apparatus internal imaging Mathematical Modeling, foundation comprises the equation group of aspect ratio parameters such as business card, text, and the method for organizing by solving an equation is obtained the aspect ratio of rectangle object and is applied in the trimming process, makes last correction result can not produce distortion.At last, by literal identification, whether the image after identification is proofreaied and correct occurs being inverted, and judges whether and need the image after proofreading and correct be rotated, thereby obtain satisfactory correction result.
As shown in Figure 1, image processing method of the present invention comprises five steps, is respectively and extracts profile, resolves profile, calculates aspect ratio, distortion correction, rectification building-out.
Extract the profile step and comprise two parts, automatic threshold is cut apart with the morphology profile and is extracted.What automatic threshold was cut apart employing is big Tianjin algorithm.Consider the difference of background in colorfulness and brightness on business card or text and next door, adopt big Tianjin algorithm to separate business card or text with background simply fast.Use big Tianjin algorithm, cromogram or gray-scale map are become binary map BW, background parts is a black on binary map BW, and business card etc. become the quadrangle of a white.Then, to binary map BW applied morphology boundary extraction method, its processing procedure is: with one 3 * 3 value is the binary map BW that the corrosion of 1 matrix obtains above entirely, obtain a new binary map BW1, deduct among the binary map BW2 that boundary profile binary map BW2. that BW1 just obtains needing in the end obtains with BW then, background and tetragonal inside become black entirely, and have only tetragonal four edges to keep white.Like this, white tetragonal boundary profile just is extracted out.
What resolve the use of profile step is the algorithm of radon change detection straight line.The radon conversion can be understood as the projection of image in ρ-θ space, the every bit correspondence image space straight line in ρ-θ space, and the radon conversion is the integration of image pixel point on every straight line, also can be regarded as the image projection on trunnion axis after the θ angle that turns clockwise.Therefore every straight line can form a bright spot in ρ-θ space in the image, and the detection of straight line is converted in the detection of ρ-θ transform domain to bright spot.Therefore, the boundary profile binary map BW2 that the profile extraction step is obtained uses the radon conversion, can find has four tangible bright spots on the radon conversion figure that obtains, they are corresponding tetragonal four edges respectively, utilize the ρ of four bright spots, the θ value, the linear equation analytic expression of four edges writes out accurately.Therefore, boundary profile is resolved successfully.The equation on two limits of simultaneous can find the solution out with the coordinate of four end points respectively.These four end points are called as input point in distortion correction.
Calculate in the aspect ratio step, at first will set up the Mathematical Modeling of imaging device internal optics imaging.As shown in Figure 2, the lens centre O of imaging device and imaging screen and irradiated area (being the imaging zone) center O ' three point on a straight line, set up coordinate system as shown in Figure 2.Wherein, lens centre and imaging region centre distance are D, and the angle on the plane at lens primary optical axis and imaging region place is θ.During shooting, the set of lenses focal length of imaging device is f, and device interior image optics coefficient is k.Fig. 3 is the plane graph of imaging region.The length of supposing rectangular article such as business card, text is l, and wide is m, and the coordinate of the center of rectangle in the imaging region coordinate system is that (x0, y0), with respect to reference axis, rectangle has rotated the α angle.For convenience of calculation, order
R = ( l 2 ) 2 + ( m 2 ) 2
∂ 1 = arctan ( m l ) - ∂
∂ 2 = arctan ( l m ) - ∂
So, in coordinate system shown in Figure 3, the coordinate of four end points of rectangle is respectively
(R×cos( 1)+x 0,R×sin( 1)×sin(θ)+y 0,-D+R×sin( 1)×cos(θ)+y 0×sin(θ))
(-R×sin( 2)+x 0,R×cos( 2)×sin(θ)+y 0,-D+R×cos( 2)×cos(θ)+y 0×sin(θ))
(R×sin( 2)+x 0,-R×cos( 2)×sin(θ)+y 0,-D-R×cos( 2)×cos(θ)+y 0×sin(θ))
(-R×cos( 1)+x 0,-R×sin( 1)×sin(θ)+y 0,-D-R×sin( 1)×cos(θ)+y 0×sin(θ))
Utilize these four end points to cross two special light that are refracted to after the lens on the imaging screen, can obtain the coordinate of the picture of these four end points on imaging screen.These two straight lines, one was the straight line of optical center of lens, and direction is constant, and other one is the straight line that is parallel to primary optical axis, crosses lens refraction afterwards through falling on the imaging screen after the overfocus.Just can obtain the coordinate of picture point according to the equation of these two straight lines.The XY coordinate of the picture point of four end points correspondences of trying to achieve behind the work in coordinate system shown in Figure 2 is respectively:
( - f × [ R × COS ( ∂ 1 ) + x 0 ] D - f - R × sin ( ∂ 1 ) × cos ( θ ) - y 0 × sin ( θ ) , - f × [ R × sin ( ∂ 1 ) × sin ( θ ) + y 0 ] D - f - R × sin ( ∂ 1 ) × cos ( θ ) - y 0 × sin ( θ ) )
( f × [ R × sin ( ∂ 2 ) - x 0 ] D - f - R × cos ( ∂ 2 ) × cos ( θ ) - y 0 × sin ( θ ) , - f × [ R × cos ( ∂ 2 ) × sin ( θ ) + y 0 ] D - f - R × cos ( ∂ 2 ) × cos ( θ ) - y 0 × sin ( θ ) )
( - f × [ R × sin ( ∂ 2 ) + x 0 ] D - f + R × cos ( ∂ 2 ) × cos ( θ ) - y 0 × sin ( θ ) , f × [ R × cos ( ∂ 2 ) × sin ( θ ) - y 0 ] D - f + R × cos ( ∂ 2 ) × cos ( θ ) - y 0 × sin ( θ ) )
( f × [ R × cos ( ∂ 1 ) - x 0 ] D - f + R × sin ( ∂ 1 ) × cos ( θ ) - y 0 × sin ( θ ) , f × [ R × sin ( ∂ 1 ) × sin ( θ ) - y 0 ] D - f + R × sin ( ∂ 1 ) × cos ( θ ) - y 0 × sin ( θ ) )
Utilize again in the step (2), the coordinate of tetragonal four end points in the image of trying to achieve, simultaneous:
- f × [ R × cos ( ∂ 1 ) + x 0 ] D - f - R × sin ( ∂ 1 ) × cos ( θ ) - y 0 × sin ( θ ) × k = x 1 - s 2
- f × [ R × sin ( ∂ 1 ) × sin ( θ ) + y 0 ] D - f - R × sin ( ∂ 1 ) × cos ( θ ) - y 0 × sin ( θ ) × k = y 1 - t 2
f × [ R × sin ( ∂ 2 ) - x 0 ] D - f - R × cos ( ∂ 2 ) × cos ( θ ) - y 0 × sin ( θ ) × k = x 2 - s 2
- f × [ R × cos ( ∂ 2 ) × sin ( θ ) + y 0 ] D - f - R × cos ( ∂ 2 ) × cos ( θ ) - y 0 × sin ( θ ) × k = y 2 - t 2
- f × [ R × sin ( ∂ 2 ) + x 0 ] D - f + R × cos ( ∂ 2 ) × cos ( θ ) - y 0 × sin ( θ ) × k = x 3 - s 2
f × [ R × cos ( ∂ 2 ) × sin ( θ ) - y 0 ] D - f + R × cos ( ∂ 2 ) × cos ( θ ) - y 0 × sin ( θ ) × k = y 3 - t 2
f × [ R × cos ( ∂ 1 ) - x 0 ] D - f + R × sin ( ∂ 1 ) × cos ( θ ) - y 0 × sin ( θ ) × k = x 4 - s 2
f × [ R × sin ( ∂ 1 ) × sin ( θ ) - y 0 ] D - f + R × sin ( ∂ 1 ) × cos ( θ ) - y 0 × sin ( θ ) × k = y 4 - t 2
Wherein, k is the scaling coefficient between imaging screen and the image, and s and t are the dimensions of image array, x1, x2, x3, x4, y1, y2, y3, y4 be respectively clapping of calculating in the step (2) image in the coordinate of four end points of white quadrangle.Like this, above equation group totally 8 unknown numbers (focal distance f is known), 8 equations, unknown number can solve respectively, like this, the ratio of l and m is that aspect ratio can be readily solved.
During distortion correction, utilize two groups of coordinate figures.One group is the coordinate figure of white tetragonal four end points of trying to achieve in step (2), another group be proofread and correct after the coordinate figure of four end points of rectangle of these four end points correspondences, this group end points is become datum mark.The upper left end points of fixed white quadrangle at first, the upper left end points of rectangle also is this point after proofreading and correct, and is motionless on the position, coordinate figure is also constant.Selecting then with the fixed endpoint is a limit of end points, calculates its length of side, and with the length of side of a this edge length of side as the rectangle after proofreading and correct, the aspect ratio that utilization is calculated above can calculate the length of side on an other limit of the rectangle after proofreading and correct.After the length and width of rectangle are all determined, utilize the coordinate of fixing point again, can respectively the coordinate Calculation of its excess-three point be come out.Therefore, the coordinate of four end points of rectangle after proofreading and correct is decided, and promptly the coordinate of datum mark is decided.Utilize the coordinate of input point and datum mark correction matrix can be obtained.Solution procedure is as follows: before supposing to proofread and correct four point coordinates for (x1, y1), (x2, y2), (x3, y3), (x4, y4), four point coordinates are (x1 ', y1 ') after proofreading and correct, (x2 ', y2 '), (x3 ', y3 '), (x4 ', y4 '), the distortion correction matrix H, H = h 11 h 12 h 13 h 21 h 22 h 23 h 31 h 32 h 33 h=(h 11,h 12,h 13,h 21,h 22,h 23,h 31,h 32,h 33) T
There is relational expression between them: x 1 y 1 1 0 0 0 - x 1 ′ x 1 - x 1 ′ y 1 - x 1 0 0 0 x 1 y 1 1 - y 1 ′ x 1 - y 1 ′ y 1 - y 1 x 2 y 2 1 0 0 0 - x 2 ′ x 2 - x 2 ′ y 2 - x 2 0 0 0 x 2 y 2 1 - y 2 ′ x 2 - y 2 ′ y 2 - y 2 x 3 y 3 1 0 0 0 - x 3 ′ x 3 - x 3 ′ y 3 - x 3 0 0 0 x 3 y 3 1 - y 3 ′ x 3 - y 3 ′ y 3 - y 3 x 4 y 4 1 0 0 0 - x 4 ′ x 4 - x 4 ′ y 4 - x 4 0 0 0 x 4 y 4 1 - y 4 ′ x 4 - y 4 ′ y 4 - y 4 × h = 0
Utilize this relational expression can solve h, corresponding distortion correction matrix H can solve.Utilize the coordinate and the distortion correction matrix of the picture element of original image to proofread and correct original image, in the image that obtains after proofreading and correct, business card and text become rectangle, and have kept original aspect ratio.
Using literal identification compensates the image after proofreading and correct.The development of present character recognition technology rapidly, and because business card or the numeral above the text all are block letter, than handwritten text identification simple a lot.The rectification building-out step comprises four parts: image segmentation, feature extraction, literal identification, judgement compensation.After image after proofreading and correct carried out preliminary treatment, image binaryzation, make the image after the binaryzation, literal etc. are black, and other backgrounds become white.The word of asking that utilizes morphology connected region method will need to discern splits, specific practice is as follows: detect first black picture element point on binary map, suppose that it is a black picture element point on the connected domain, its beginning as recursive procedure, recurrence formula is: X k=(X K-1 B) ∩ A, X kThe connected region that representative extracts, the binary map above the A representative, B is one 3 * 38 connected region templates.After satisfactory connected region is found out with all, carry out normalization again, all connected regions are all carried out interpolation become 20 * 10 matrix.Because the overwhelming majority comprises Arabic numerals in business card or the text, so the present invention discerns Arabic numerals emphatically.If do not have numeral in business card or the text, can discern English alphabet and Chinese character successively so.For example, when the present invention discerns numeral, by to 2,3,4,5,7 (because 0,1,6,8, even 9 be inverted and also have corresponding digital corresponding with it, for example, 0 and 0,6 and 9, or the like.) analysis of feature, adopt four kinds of numerical characteristics: the horizontal line feature, vertical line feature, horizontal direction are crossed the line number, and vertical direction is crossed the line number, and these digital numerical characteristics are as shown in table 1 below.Therefore, set up the respective classified device, as shown in the following Table 2, can be respectively with these digit recognition.For example, identify numeral 2 now, explanation so, business cards etc. are not inverted, if, utilize grader not identify numeral, explanation so, business cards etc. are inverted.Therefore, need the image after proofreading and correct be rotated again, the image that obtains then is only last needs.
Table 1 is the numerical characteristic form.
Numerical characteristic 2 3 4 5 7
The horizontal line feature Last horizontal line 0 0 0 1 1
Following horizontal line 1 0 0 0 0
The vertical line feature Left side vertical line 0 0 0 0 0
Right vertical line 0 0 0 0 0
Horizontal direction is crossed the line feature Went up the line number 2 2 2 1 2
Played the line number 2 2 1,2 2 1
Vertical direction is crossed the line feature The line number is crossed on a left side 4,3 2,3,4 2,3 4,3 1,2
The right line number of crossing 3 4 2 3 2
Table 2 is the digital sort device.
Numerical characteristic 2 3 4 5 7
Last horizontal line 0 0 0 1 1
Following horizontal line 1 0 0 0 0
Left side vertical line 0 0 0 0 0
Right vertical line 0 0 0 0 0
Went up the line number 2 2 2 1 2
The right line number of crossing 3 4 2 3 2
Last 1/3 highly located the line number 1 1 2 1 1
The present invention can be used as the central processing module that the distortion correction submodule embeds imaging device inside, makes imaging device have the automatic distortion correction function.Its implementation is, the distortion correction submodule is embedded in the central processing module of imaging device as function sub-modules, on hardware, share identical digital signal processing chip with central processing module, use digital image processing method of the present invention on the software, on function, realize automatic distortion correction.

Claims (6)

1, a kind of picture distortion is characterized in that from the image processing method of dynamic(al) correction, comprises five steps:
(1) extracts profile: utilize big Tianjin algorithm to carry out automatic threshold and cut apart, adopt morphological method to carry out edge contour and extract;
(2) resolve profile: utilize the radon conversion will go up edge contour that the step extracts and separate out, and try to achieve the coordinate of four end points with the formal solution of linear equation;
(3) calculate aspect ratio: be created as the Mathematical Modeling of picture device interior optical imagery, utilize optical imagery knowledge, set up equation group, try to achieve aspect ratio;
(4) distortion correction: utilize two groups of coordinates to try to achieve the distortion correction matrix image is proofreaied and correct, the aspect ratio of image remains unchanged in the trimming process;
(5) rectification building-out: in the time of digital above the method for utilizing digit recognition is judged the image after proofreading and correct inverted phenomenon takes place, select whether need image rotating, the image of finishing after the correction can not proofreaied and correct.
2, picture distortion according to claim 1 is from the image processing method of dynamic(al) correction, it is characterized in that, described extraction profile step comprises two parts: automatic threshold is cut apart with the morphology profile and is extracted, at first adopting big Tianjin algorithm that image is carried out automatic threshold cuts apart, obtain a binary map, on binary map, business card, text become white, and background in addition becomes black; Utilize morphological method, white portion is handled, only stay white tetragonal edge contour, like this, profile extracts and finishes.
3, picture distortion according to claim 1 is from the image processing method of dynamic(al) correction, it is characterized in that, in the described parsing profile step, utilize the radon conversion to parse the ρ-θ spatial information of four white edge straight lines on the binary map, the linear equation of four white edges is obtained, utilize the method for the group of solving an equation then, the coordinate of four end points is found the solution out.
4, picture distortion according to claim 1 is characterized in that from the image processing method of dynamic(al) correction, in the described calculating aspect ratio step, by being created as the Mathematical Modeling of picture device interior optical imagery, sets up following equation group:
- f × [ R × cos ( ∂ 1 ) + x 0 ] D - f - R × sin ( ∂ 1 ) × cos ( θ ) - y 0 × sin ( θ ) × k = x 1 - s 2
- f × [ R × sin ( ∂ 1 ) × sin ( θ ) + y 0 ] D - f - R × sin ( ∂ 1 ) × cos ( θ ) - y 0 × sin ( θ ) × k = y 1 - t 2
f × [ R × sin ( ∂ 2 ) - x 0 ] D - f - R × cos ( ∂ 2 ) × cos ( θ ) - y 0 × sin ( θ ) × k = x 2 - s 2
- f × [ R × cos ( ∂ 2 ) × sin ( θ ) + y 0 ] D - f - R × cos ( ∂ 2 ) × cos ( θ ) - y 0 × sin ( θ ) × k = y 2 - t 2
- f × [ R × sin ( ∂ 2 ) + x 0 ] D - f + R × cos ( ∂ 2 ) × cos ( θ ) - y 0 × sin ( θ ) × k = x 3 - s 2
f × [ R × cos ( ∂ 2 ) × sin ( θ ) - y 0 ] D - f + R × cos ( ∂ 2 ) × cos ( θ ) - y 0 × sin ( θ ) × k = y 3 - t 2
f × [ R × cos ( ∂ 1 ) - x 0 ] D - f + R × sin ( ∂ 1 ) × cos ( θ ) - y 0 × sin ( θ ) × k = x 4 - s 2
f × [ R × sin ( ∂ 1 ) × sin ( θ ) - y 0 ] D - f + R × sin ( ∂ 1 ) × cos ( θ ) - y 0 × sin ( θ ) × k = y 4 - t 2
Wherein, the long l of rectangle, wide m, lens centre and imaging region centre distance are D, the angle on the plane at lens primary optical axis and imaging region place is θ, known focal distance f, and the coordinate of the center of rectangle in the imaging region coordinate system is (x0, y0), with respect to reference axis, rectangle has rotated the α angle, and k is the scaling coefficient between imaging screen and the image, s and t are the dimensions of image array, x1, x2, x3, x4, y1, y2, y3, y4 be respectively clapping of calculating in the step (2) image in the coordinate of four end points of white quadrangle, suppose
R = ( l 2 ) 2 + ( m 2 ) 2
∂ 1 = arctan ( m l ) - ∂
∂ 2 = arctan ( l m ) - ∂
Like this, top equation group can be separated, and these parametric solutions come out, and just can obtain the aspect ratio of rectangle.
5, picture distortion according to claim 1 is from the image processing method of dynamic(al) correction, it is characterized in that, described distortion correction step, the coordinate figure that at first utilizes four end points that calculate in the step (2) is as input point, utilize input point and aspect ratio that datum mark is calculated, utilize two groups of coordinate figures that the distortion correction matrix H is obtained then, utilize the distortion correction matrix that original image is proofreaied and correct again, rectangle keeps aspect ratio constant in the image after proofreading and correct.
6, picture distortion according to claim 1 is from the image processing method of dynamic(al) correction, it is characterized in that, in the described rectification building-out step, adopt the algorithm of literal identification to compensate, if correctly identify numeral or English alphabet in the recognition result, do not need rotation correction image afterwards so,, need so image is rotated correction if recognition result does not identify numeral or English alphabet.
CN 200610117277 2006-10-19 2006-10-19 Image processing method for image distortion automatic correction Pending CN1937698A (en)

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Cited By (36)

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CN104427234A (en) * 2013-09-02 2015-03-18 联想(北京)有限公司 Image distortion correction method and electronic device
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CN106991649A (en) * 2016-01-20 2017-07-28 富士通株式会社 The method and apparatus that the file and picture captured to camera device is corrected
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CN108537146A (en) * 2018-03-22 2018-09-14 五邑大学 A kind of block letter mixes line of text extraction system with handwritten form
CN108805124A (en) * 2018-04-18 2018-11-13 北京嘀嘀无限科技发展有限公司 Image processing method and device, computer readable storage medium
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CN101256627B (en) * 2008-01-25 2011-12-28 浙江工业大学 Method for analysis of picture distortion based on constant moment
WO2011003315A1 (en) * 2009-07-08 2011-01-13 中兴通讯股份有限公司 Mobile terminal based image processing method and mobile terminal
CN101989349A (en) * 2009-08-03 2011-03-23 夏普株式会社 Image output apparatus and method, portable terminal apparatus and captured image processing system
CN101989349B (en) * 2009-08-03 2012-10-10 夏普株式会社 Image output apparatus and method and captured image processing system
CN101807293A (en) * 2010-03-19 2010-08-18 上海合合信息科技发展有限公司 Method for adjusting detection result of image quadrilateral frame
US9082192B2 (en) 2010-12-10 2015-07-14 Intsig Information Co., Ltd Text image trimming method
WO2012075817A1 (en) * 2010-12-10 2012-06-14 上海合合信息科技发展有限公司 Text image trimming method
CN102073997A (en) * 2011-01-12 2011-05-25 东华理工大学 Small-square document image perspective-recovery method
CN102073997B (en) * 2011-01-12 2012-11-07 东华理工大学 Small-square document image perspective-recovery method
CN103139438B (en) * 2011-11-21 2015-06-03 株式会社Pfu Image processing apparatus and image processing method
CN103139438A (en) * 2011-11-21 2013-06-05 株式会社Pfu Image processing apparatus and image processing method
CN102750669A (en) * 2012-05-29 2012-10-24 山东神思电子技术股份有限公司 Image rotation processing method
CN102750669B (en) * 2012-05-29 2014-07-09 山东神思电子技术股份有限公司 Image rotation processing method
CN103106634A (en) * 2012-12-26 2013-05-15 上海合合信息科技发展有限公司 Method and system for protecting bank card individual information
CN104427234A (en) * 2013-09-02 2015-03-18 联想(北京)有限公司 Image distortion correction method and electronic device
CN103679700A (en) * 2013-10-29 2014-03-26 成都三泰电子实业股份有限公司 Bill image inversion detection system
CN103679700B (en) * 2013-10-29 2016-09-07 成都三泰控股集团股份有限公司 Bill image inversion detection system
CN105590298A (en) * 2014-11-07 2016-05-18 三星电子株式会社 Extracting and correcting image data of an object from an image
CN105590298B (en) * 2014-11-07 2021-06-11 三星电子株式会社 Extracting and correcting image data of an object from an image
CN106991649A (en) * 2016-01-20 2017-07-28 富士通株式会社 The method and apparatus that the file and picture captured to camera device is corrected
CN109479082A (en) * 2016-12-21 2019-03-15 华为技术有限公司 Image processing method and device
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CN106846607A (en) * 2017-01-11 2017-06-13 深圳怡化电脑股份有限公司 A kind of Paper Currency Identification and device
CN106952231A (en) * 2017-03-20 2017-07-14 南京大学 A kind of image real time correction method based on cell phone platform
CN106952231B (en) * 2017-03-20 2019-06-11 南京大学 A kind of image real time correction method based on cell phone platform
CN107096720A (en) * 2017-06-22 2017-08-29 西安科技大学 Express mail bar code automatic recognition system and method based on image procossing
CN107096720B (en) * 2017-06-22 2022-11-29 西安科技大学 Express item bar code automatic identification system and method based on image processing
CN111480104A (en) * 2017-10-10 2020-07-31 视界工程有限公司 Stereomicroscope with single objective
CN107944324A (en) * 2017-11-16 2018-04-20 凌云光技术集团有限责任公司 A kind of Quick Response Code distortion correction method and device
CN108320270B (en) * 2018-01-26 2023-12-29 腾讯科技(深圳)有限公司 Image correction method, device and storage medium
CN108320270A (en) * 2018-01-26 2018-07-24 腾讯科技(深圳)有限公司 A kind of method for correcting image, device and storage medium
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CN108537146A (en) * 2018-03-22 2018-09-14 五邑大学 A kind of block letter mixes line of text extraction system with handwritten form
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CN108510463B (en) * 2018-05-07 2020-12-25 凌云光技术股份有限公司 Method and device for correcting distorted image
CN108510463A (en) * 2018-05-07 2018-09-07 凌云光技术集团有限责任公司 A kind of antidote and device of fault image
CN109214389A (en) * 2018-09-21 2019-01-15 上海小萌科技有限公司 A kind of target identification method, computer installation and readable storage medium storing program for executing
CN109214389B (en) * 2018-09-21 2021-09-28 上海小萌科技有限公司 Target identification method, computer device and readable storage medium
CN109409366B (en) * 2018-10-30 2022-04-05 四川长虹电器股份有限公司 Distorted image correction method and device based on angular point detection
CN109409366A (en) * 2018-10-30 2019-03-01 四川长虹电器股份有限公司 Distorted image correction method and device based on Corner Detection
CN109754381A (en) * 2019-01-03 2019-05-14 广东小天才科技有限公司 Image processing method and system
CN110097054A (en) * 2019-04-29 2019-08-06 济南浪潮高新科技投资发展有限公司 A kind of text image method for correcting error based on image projection transformation
CN110505398A (en) * 2019-07-16 2019-11-26 北京三快在线科技有限公司 A kind of image processing method, device, electronic equipment and storage medium
CN110991454A (en) * 2019-12-23 2020-04-10 云南大学 Blade image recognition method and device, electronic equipment and storage medium
CN111814802B (en) * 2020-08-31 2021-01-26 创新奇智(南京)科技有限公司 Character image processing method and device, storage medium and electronic equipment
CN111932483A (en) * 2020-09-28 2020-11-13 江西汉辰信息技术股份有限公司 Picture processing method and device, storage medium and computer equipment
CN114485389A (en) * 2020-10-26 2022-05-13 住友重机械工业株式会社 Distortion aberration correction processing device, distortion aberration correction method, and storage medium
CN115760620B (en) * 2022-11-18 2023-10-20 荣耀终端有限公司 Document correction method and device and electronic equipment
CN115760620A (en) * 2022-11-18 2023-03-07 荣耀终端有限公司 Document correction method and device and electronic equipment
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