JP2008204179A - Document evaluation device, program and storage medium - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a technology for objectively evaluating a design property of a document. <P>SOLUTION: This document evaluation device has an object acquiring means for acquiring the positions of objects included in the document to be evaluated; a coincidence degree calculation means for calculating the degree of coincidence between an object graphic defined by feature points determined by the positions of the objects acquired by the object acquiring means, and a predetermined reference graphic; and an evaluation means for evaluating the document based on the degree of coincidence calculated by the coincidence degree calculation means. <P>COPYRIGHT: (C)2008,JPO&INPIT

Description

  The present invention relates to a technique for evaluating a document.

  Systems that support the creation of documents have been developed. These systems are intended to create documents with a clean and balanced design that are irrelevant to the user's knowledge and experience. In order to create a beautiful document, it is necessary to evaluate what kind of document is beautiful, that is, the design of the document.

  For example, Patent Documents 1 to 5 are known as techniques for evaluating a document. Patent Document 1 discloses a technique for accumulating evaluations of documents input by a user. Patent Document 2 discloses a technique for changing a layout based on evaluation of a document input by a user. Patent Document 3 discloses a technique for generating a layout according to the design of a document. Patent Document 4 discloses a technique for evaluating a document by capturing a user's line of sight. Patent Document 5 discloses a technique for evaluating a document based on the degree of association between a plurality of illustrations included in the document.

JP-A-9-212493 JP 2000-263872 A JP 2000-289282 A JP 2002-123504 A JP 2002-269070 A

Patent Documents 1 to 4 evaluate a document based on the subjectivity of the user, and do not objectively evaluate the document. Patent document 5 evaluates the degree of association between illustrations, and does not evaluate a document.
In contrast, the present invention provides a technique for objectively evaluating a document.

In order to solve the above-described problem, the present invention provides an object acquisition unit that acquires the position of an object included in a document to be evaluated, and a figure formed by a feature point determined by the position of the object acquired by the object acquisition unit A matching degree calculating means for calculating a matching degree between the target figure and a predetermined reference figure, and an evaluation means for evaluating the document based on the matching degree calculated by the matching degree calculating means. A document evaluation apparatus is provided.
According to this document evaluation apparatus, a document is evaluated based on the matching degree between the reference graphic and the target graphic.

In a preferred aspect, in the document evaluation apparatus, the reference graphic may be a golden dividing line that divides between two reference lines into a golden ratio.
According to this document evaluation apparatus, a document is evaluated based on the degree of coincidence between the target graphic and the golden dividing line.

In another preferred aspect, in the document evaluation apparatus, the side of the reference graphic may be a golden dividing line of a layout area that is an area in which an object is arranged in the document.
According to this document evaluation apparatus, a document is evaluated based on the degree of coincidence between a line that divides golden between two boundary lines of a layout area and a target graphic.

In still another preferred aspect, in the document evaluation apparatus, the object acquisition unit acquires the size or shape in addition to the position of the object, and at least one of the two reference lines is acquired by the object acquisition unit. It may be determined based on the position, size, or shape of the object.
According to this document evaluation apparatus, a document is evaluated based on the degree of coincidence between a line dividing the golden line between the boundary line of the layout area and the object and the target graphic.

In still another preferred aspect, the document evaluation apparatus is configured such that the document includes a plurality of objects, and the target graphic is a graphic formed by a plurality of feature points determined by positions, sizes, or shapes of the plurality of objects. May be.
According to this document evaluation apparatus, the target graphic is defined by feature points extracted from a plurality of objects.

In still another preferred aspect, in the document evaluation apparatus, the figure formed by the plurality of special vertices may be a golden triangle, a golden rectangle, or a golden pentagon.
According to this document evaluation apparatus, a document is evaluated based on the degree of coincidence between the target graphic and the golden triangle, golden rectangle, or golden pentagon.

In still another preferred aspect, the document evaluation apparatus is characterized in that the document includes a plurality of objects, each of the plurality of objects has attribute information indicating its attribute, and a reference graphic shape and feature point extraction condition Storage means for storing a plurality of data sets that correspond to each other, and the coincidence calculation means has a plurality of matches for a plurality of sets of reference figures and target figures corresponding to the plurality of data sets stored in the storage means. The degree may be calculated, and the evaluation unit may evaluate the document based on the plurality of matching degrees.
According to this document evaluation apparatus, a document is evaluated based on the degree of coincidence between a plurality of sets of reference graphics and target graphics.

In still another preferred aspect, in this document evaluation apparatus, the data set includes a weighting coefficient corresponding to each reference graphic, and the evaluation means calculates a weighting coefficient included in the data set for the degree of coincidence with each reference graphic. The document may be evaluated based on a result of a weighting operation to be multiplied.
According to this document evaluation apparatus, a document is evaluated on the basis of the degree of coincidence between a plurality of sets of reference graphics and target graphics by weighting calculation.

According to another aspect of the present invention, a computer apparatus is configured to acquire a position of an object included in a document to be evaluated, a target figure that is a figure formed by a feature point defined by the acquired position of the object, and a predetermined figure. There is provided a program for executing a step of calculating a degree of coincidence with a calculated reference figure and a step of evaluating the document based on the calculated degree of coincidence.
Furthermore, the present invention provides a storage medium storing the above program.
According to this program, a document is evaluated based on the matching degree between the reference graphic and the target graphic.

1. Configuration FIG. 1 is a diagram illustrating a functional configuration of a document evaluation apparatus 100 according to an embodiment. The document evaluation apparatus 100 evaluates a document. In particular, the document evaluation apparatus 100 evaluates a document based on the position of an object or the relative positions of a plurality of objects. The “document” refers to data including layout information indicating the arrangement of at least one object arranged in the layout area and the object in the layout area, or a result output according to the data. “Object” refers to data indicating at least one of text (character string) or image, or text or image indicated by the data. The “layout area” means a physical boundary of an output document or an area where an object is arranged. The layout area refers to, for example, one or a plurality of papers on which a document is printed, one page, a plurality of continuous pages, a partial area of a page, or a printing plate.

  The object acquisition unit 101 acquires the position of an object included in a document to be evaluated (hereinafter referred to as “target document”). The reference graphic storage unit 102 stores a graphic (hereinafter referred to as “reference graphic”) that serves as a reference for evaluation. The degree of coincidence calculation unit 103 calculates the degree of coincidence between a figure formed by a feature point determined by the position of an object (hereinafter referred to as “target figure”) and a reference figure. The evaluation unit 104 evaluates the document based on the degree of coincidence.

  FIG. 2 is a diagram illustrating a hardware configuration of the document evaluation apparatus 100. A CPU (Central Processing Unit) 110 is a control device that controls each element of the document evaluation device 100. A ROM (Read Only Memory) 120 is a storage device that stores data and programs necessary for starting up the document evaluation apparatus 100. A RAM (Random Access Memory) 130 is a storage device that functions as a work area when the CPU 110 executes a program. An I / F (Interface) 140 is an interface for inputting / outputting data and control signals to / from various input / output devices and storage devices. An HDD (Hard Disk Drive) 150 is a storage device that stores various programs and data. Regarding the present embodiment, the HDD 150 stores a document evaluation program for generating grid lines. The keyboard / mouse 160 is an input device for a user to input an instruction to the document evaluation device 100. The display 170 is an output device that displays data contents or processing status. In the present embodiment, the display 170 displays objects, layout areas, and grid lines. The network IF 180 is an interface for transmitting and receiving data to and from other devices connected via a network (not shown). For example, the document evaluation apparatus 100 can receive a document (more precisely, electronic data indicating the document) via the network and the network IF 180. CPU 110, ROM 120, RAM 130, and I / F 140 are connected via a bus 190. When the CPU 110 executes the document evaluation program, the document evaluation apparatus 100 has the functional configuration shown in FIG. The document evaluation apparatus 100 may be any apparatus as long as it includes the functional configuration shown in FIG. 1 and the hardware configuration shown in FIG. For example, the document evaluation apparatus 100 is a so-called personal computer. Alternatively, the document evaluation apparatus 100 may be an image forming measure such as a printer. A part of the hardware configuration shown in FIG. 2 may be omitted.

2. Operation FIG. 3 is a flowchart showing the operation of the document evaluation apparatus 100. In step S100, the CPU 110 acquires the position of the object. In the present embodiment, the CPU 110 acquires an object and its position while being included in the target document. The HDD 150 stores a document. CPU 110 reads a document from HDD 150.

FIG. 4 is a diagram illustrating an acquired document. The document D ₁ includes objects T ₁ , T _2, and I ₁ in the layout area L. Object T ₁ includes a character string and the attribute "golden ratio is beautiful." The object T ₁ has information indicating the object type “text”, the category “title”, and the size of the object as its attributes. Object T ₂ is, as its attributes, objects of type "text", has information indicating the size of the category "body" and the object. Object I ₁ includes an image and its attributes. The object I ₁ has information indicating the object type “image”, the category “main image”, and the size of the object as its attributes. Further, the document D ₁ includes information (hereinafter referred to as “layout information”) indicating the arrangement of each object in the layout area L.

  A description will be given with reference to FIG. 3 again. In step S110, CPU 110 calculates an evaluation value. Details are as follows.

FIG. 5 is a flowchart showing details of the evaluation value calculation process. In step S111, the CPU 110 acquires a reference graphic. In the present embodiment, the reference graphic is a golden dividing line, a golden triangle, a golden rectangle, and a golden pentagon. The golden dividing line is a line that divides between two reference lines into a golden ratio. A golden triangle is a triangle whose base length to height ratio is the golden ratio. A golden rectangle is a quadrangle whose length ratio between two adjacent sides is the golden ratio. The golden pentagon is a regular pentagon in which a triangle formed by diagonal lines is a golden triangle. The HDD 150 stores parameters for specifying these reference graphics (for example, the ratio of the length and height of the base in a triangle). CPU 110 reads parameters from HDD 150. The “golden ratio” refers to a ratio (about 1: 1.618) represented by the following formula (1). The right term and the left term of Formula (1) may be interchanged.

  In step S112, the CPU 110 initializes the evaluation value Pt. Here, the CPU 110 initializes Pt = 0.

  In step S113, the CPU 110 calculates a target graphic based on the feature points. First, the CPU 110 extracts feature points from the object. Which point is used as a feature point in each object is determined in advance. Further, from which object the feature points are extracted is determined in advance. Furthermore, the shape of the target graphic is also determined in advance. In the present embodiment, vertices that are far from other objects among the vertices of the boundary line of the object are used as feature points. The feature points are extracted from the object whose category is “title” or “main image”. Furthermore, the shape of the target graphic is a triangle, a quadrangle, or a pentagon.

In the present embodiment, objects whose feature points are to be extracted are objects whose category is “title” or “main image”, that is, the objects T ₁ and I ₁ . As shown in FIG. 4, the object T ₁ (the boundary line or circumscribed polygon thereof) has four vertices of points P _{1 to} P ₄ . The CPU 110 extracts points P ₁ and P ₂ that are vertices far from the other object from which the feature points are extracted, that is, the object I _1, as feature points. Similarly, the object I ₁ (the boundary line or circumscribed polygon) has four vertices of points P _{5 to} P ₈ . The CPU 110 extracts points P ₇ and P ₈ that are vertices far from the object T ₁ , that is, the distance from the object T _1, as feature points.

The CPU 110 determines the shape of the target graphic according to the number of feature points. Now that a total of four feature points have been extracted, the CPU 110 determines the shape of the target graphic to be a rectangle. The CPU 110 generates the target graphic according to a predetermined condition. In the present embodiment, “polygon having feature points as vertices” is used as a condition for generating the target graphic. That is, the CPU 110 generates a trapezoid S ₁ having points P ₁ , P ₂ , P ₇ and P ₈ as vertices as the target graphic.

  In step S114, the CPU 110 calculates the degree of coincidence between the target graphic and the reference graphic. Details are as follows.

FIG. 6 is a flowchart showing details of the matching degree calculation process. In step S1141, the CPU 110 calculates parameters according to the reference graphic. The HDD 150 stores the shape of the reference graphic and a parameter calculation method corresponding to the shape. Here, the HDD 150 stores the use of the ratio of the base of the quadrangle to the height as the parameter a corresponding to the quadrangle. CPU110 is in accordance with the stored data in the HDD 150, here, it calculates the base and the ratio of the height of the trapezoid _{S 1} as a parameter a.

  In step S1142, CPU 110 determines whether the parameter in the reference graphic is the golden ratio. When the parameter in the reference graphic is the golden ratio (S1142: YES), the CPU 110 shifts the processing to step S1143. When the parameter in the reference graphic is not the golden ratio (S1142: NO), the CPU 110 shifts the processing to step S1144. In this example, since the parameter, that is, the ratio of the base to the height, is the golden ratio in the golden rectangle that is the reference graphic, the CPU 110 shifts the processing to step S1143.

In step S <b> 1143, the CPU 110 calculates the matching degree α according to a predetermined mathematical formula. Here, the following equation (2) is used. Here, the degree of coincidence α is a real number that satisfies 0 ≦ α ≦ 1.
α = Min (r _g , a) / Max (r _g , a) (2)
Here Min _(r g, a) and Max _(r g, a) shows the minimum and maximum ones of the _{r g} and a. r _g is the golden ratio. For example, when the parameter a is 1.50, the matching degree α is calculated as follows.
α = 1.50 / 1.618 = 0.927
The process of step S1144 will be described later.

  A description will be given with reference to FIG. 5 again. In step S115, the CPU 110 calculates the evaluation value of the document. Here, the degree of coincidence calculated in step S1143 is used as an evaluation value as it is. That is, Pt = α = 0.927.

  A description will be given with reference to FIG. 3 again. In step S120, CPU 110 outputs an evaluation result. For example, the CPU 110 displays the evaluation result on the display 170. Alternatively, the CPU 110 may store data indicating the evaluation result in the RAM 130. Further alternatively, the CPU 110 may output data indicating the evaluation result to another device via the network IF 180.

  For example, the document evaluation apparatus may output the evaluation result to a document editing apparatus that edits a document. The document editing apparatus may select an optimum editing result from a plurality of candidates based on the evaluation result.

FIG. 7 is a diagram illustrating a document to be evaluated. In this example, the layout of the document is evaluated based on the relative position of the object T ₁ whose category is “title” and the object I ₁ whose category is “main image”. The target figure is indicated by a dotted line.
As described above, according to the present embodiment, the document layout is objectively evaluated.

3. Other Embodiments The present invention is not limited to the above-described embodiments, and various modifications can be made. In the following, description of matters common to the embodiment will be omitted. In addition, elements common to the embodiment will be described using common reference numerals.

3-1. Modification 1
The number of reference figures used for calculating the evaluation value is not limited to one. In the above-described embodiment, the evaluation value is calculated using one reference rectangle selected from the golden dividing line, the golden triangle, the golden rectangle, and the golden pentagon. However, the evaluation value may be calculated using a plurality of reference figures.

  FIG. 8 is a flowchart showing details of the evaluation value calculation processing according to the first modification. In the first modification, the flow of FIG. 8 is used instead of the flow of FIG. In step S200, CPU 110 acquires a reference graphic. The process of step S200 is performed similarly to the process of step S111. In step S201, the CPU 110 initializes the evaluation value Pt and the variable Ti. The variable Ti is a parameter that specifies the reference graphic. Here, the CPU 110 initializes Pt = 0 and Ti = 1. The reference graphic specified by the variable Ti is represented as a reference graphic (Ti). The reference figure (1) is a golden triangle, the reference figure (2) is a golden rectangle, and the reference figure (3) is a golden pentagon.

  In step S202, the CPU 110 calculates a target graphic based on feature points. The HDD 150 stores a target graphic table having a reference graphic, a condition of a feature point corresponding to the reference graphic, a method of forming the target graphic from the feature point, and the number of reference points of the reference graphic. The CPU 110 calculates a target graphic (Ti) corresponding to the reference graphic (Ti) with reference to the target graphic table.

  FIG. 9 is a diagram illustrating a target graphic table. First, since Ti = 1, the reference graphic is a golden triangle. In accordance with the target graphic table, the CPU 110 extracts a total of three points from the center of gravity of the title and two vertices of the main image that are far from the title object as feature points. Further, the CPU 110 calculates a triangle having three feature points as vertices as a target graphic.

FIG. 10 is a diagram illustrating a target graphic. And _{P 9} point is the centroid of the object _{T 1, P 7} and _{P 8} point distance is long between the object _{T 1} of the vertex of the object _{I 1} is the characteristic point. The target figure is indicated by a dotted line.

A description will be given with reference to FIG. 8 again. In step S203, the CPU 110 calculates the degree of coincidence between the reference graphic (Ti) and the target graphic (Ti). The details of this processing are the same as those described with reference to FIG.
In step S204, the CPU 110 calculates an evaluation value Pt by the following equation (3).
Pt = Pt + c (Ti) × α (Ti) (3)
c (Ti) is the number of reference points corresponding to the reference figure (Ti). α (Ti) is the number of reference points for the reference figure (Ti). The initial value of Pt is 0. From the table of FIG. 9, c (1) = 20. When α (1) = 0.90, the evaluation value Pt is calculated as follows.
Pt = 0 + 20 × 0.90 = 18

  In step S205, the CPU 110 determines whether the processing has been completed for all the reference graphics. When it is determined that there is a reference graphic that has not yet been processed (S205: NO), in step S206, the CPU 110 updates the variable Ti to Ti = Ti + 1. When it is determined that the process has been completed for all the reference graphics (S205: YES), the CPU 110 ends the process of FIG. In this example, the golden rectangle and the golden pentagon have not been processed yet. Therefore, in step S206, the CPU 110 updates the variable Ti to Ti = 2.

  When the variable Ti is updated, the CPU 110 shifts the processing to step S202. Since Ti = 2 now, the reference figure is a golden rectangle. In accordance with the target graphic table, the CPU 110 extracts a total of four points, ie, two points far from the main image object from the title vertices and two points far from the title object from the main image vertices as feature points. Further, the CPU 110 calculates a quadrangle having four feature points as vertices as a target graphic.

FIG. 11 is a diagram illustrating a target graphic. Among the vertices of the object T ₁ , points P ₁ and P ₂ that are far from the object I ₁ and among the vertices of the object I ₁ , points P ₇ and P ₈ that are far from the object T ₁ are feature points. The target figure is indicated by a dotted line.

A description will be given with reference to FIG. 8 again. In step S203, the CPU 110 calculates the degree of coincidence between the reference graphic (Ti) and the target graphic (Ti).
In step S204, the CPU 110 calculates an evaluation value Pt using equation (3).
The evaluation value Pt is now 18. From the table of FIG. 9, c (2) = 60. When α (2) = 0.927, the evaluation value Pt is calculated as follows.
Pt = 18 + 60 × 0.927 = 73.6

  Since the golden pentagon has not yet been processed, the determination result in step S205 is “NO”. In step S206, the CPU 110 updates the variable Ti to Ti = 3. When the variable Ti is updated, the CPU 110 shifts the processing to step S202. Since Ti = 3 now, the reference figure is a golden pentagon. The CPU 110, in accordance with the target graphic table, is the midpoint of the side parallel to the title centerline among the sides constituting the boundary of the layout area, and the two end points of the title centerline that are far from the main image object. Of the vertices and the vertices of the main image, a total of five points that are far from the title object are extracted as feature points. Further, the CPU 110 calculates a pentagon having five feature points as vertices as a target graphic.

FIG. 12 is a diagram illustrating a target graphic. Upper midpoint at which point _{P 10} of the layout area L, a point the distance between the object _{T 1} of the vertices of the object _{T 1} of the center line _{L C} point _{P 11} and the point _{P 12} on both ends of and the object _{I 1,} is long P ₇ and P ₈ are feature points. The target figure is indicated by a dotted line.

  A description will be given with reference to FIG. 8 again. In step S203, the CPU 110 calculates the degree of coincidence between the reference graphic (Ti) and the target graphic (Ti). When the reference graphic and the target graphic are pentagons, the coincidence is calculated as follows, for example. Since the pentagon has five sides, there can be five triangles having each side and two diagonal lines as sides. The CPU 110 calculates the ratio of the base to the height for each triangle. CPU 110 calculates the degree of coincidence according to equation (3). The CPU 110 sets the average value of the matching degrees calculated for the five triangles as the pentagonal matching degree.

In step S204, the CPU 110 calculates an evaluation value Pt using equation (3).
Now, the value of the evaluation value Pt is 73.6. From the table of FIG. 9, c (3) = 20. When α (3) = 0.20, the evaluation value Pt is calculated as follows.
Pt = 73.6 + 20 × 0.20 = 77.6

As described above, since the processing for the golden triangle, the golden rectangle, and the golden pentagon is completed, the determination in step S205 is “YES”.
Thus, according to the modification 1, an evaluation value is calculated using a plurality of reference figures.

  In the above example, when the evaluation value for each reference graphic is calculated, the reference score and the evaluation value are integrated. That is, a weighting factor is set for each reference graphic and a weighting operation is performed. However, the evaluation value for each reference graphic may be simply added.

3-2. Modification 2
The shape of the reference graphic is not limited to the golden polygon. Here, an example in which the reference graphic is a golden dividing line will be described. The target graphic is a feature point extracted from a predetermined object, for example, the upper left point of an object whose category is “title”. The target graphic is a concept including points, lines, and polygons. When the reference graphic is a golden dividing line, the determination result in step S1142 of FIG. 6 is “NO”.

In step S1144, the CPU 110 calculates the coincidence α according to the following equation (4).
α = 1−b / b _ref (4)
Here, the parameter b is the difference between the golden dividing line and the coordinates of the object in the vertical direction of the layout area. The parameter b _ref is a reference value, for example, the vertical length of the layout area. When the parameter b is a coordinate difference in the horizontal direction of the layout area, the parameter b _ref is the length of the layout area in the horizontal direction.

FIG. 13 is a diagram for explaining a matching score calculation method according to the second modification. Grid lines G ₁ is a grid line dividing between the upper edge of the upper side and the object T ₂ of the layout area to the golden ratio. The parameter b is the difference between the y coordinate of the object T _{1 and} the y coordinate of the grid line G ₁ . Note y coordinate of the object T ₁ is determined by the position of the upper left corner.

3-3. Modification 3
The method for calculating the degree of coincidence is not limited to that described with reference to FIG. Any method may be used as long as it can objectively express the degree of matching between the target graphic and the reference graphic. For example, a value obtained by superimposing the target graphic and the reference graphic with a certain point as a reference and dividing the area of the portion where the two do not match by the area of the reference graphic from 1 may be used as the degree of coincidence. .

FIG. 14 is a diagram for explaining a coincidence degree calculation method according to the third modification. The size of the reference graphic P _S are that predetermined, for example, points at both ends of the base are determined so as to coincide with the target figure P _T. The hatched portion in FIG. 14 is a portion that reference figure P _S and the subject graphic P _T does not match. The degree of coincidence α is calculated, for example, according to the following equation (5).
α = 1−S _N / S _S (5)
Note S _N is the area of the portion not coincident, S _S indicates the area of the reference graphic P _S. Area of the subject graphic P _T instead of the area of the reference graphic P _S may be used as the S _S.

3-4. Modification 4
The number of objects used for calculating the evaluation value may not be plural. In Modification 2, the example in which the reference graphic is a golden grid line has been described. In this example, the feature points are extracted only from the object whose category is “title”. However, it is not limited to the case where the reference graphic is a golden grid line. In other cases, feature points may be extracted from only a single object. For example, four vertices of the boundary line of an object whose category is “text” may be extracted as feature points. In this case, the document is evaluated based on the degree of coincidence between the quadrangle formed by the four vertices and the golden rectangle.

3-5. Other Modifications The above embodiment and Modifications 1 to 4 may be used in combination.

  In step S100, the object may not be acquired together with the target document. That is, each object and layout information need not be acquired simultaneously from the same source. The object and the target document may be acquired from another device via the network and the network IF 180, for example. Alternatively, the object and the target document may be input by the user operating the keyboard / mouse 160.

  The target graphic table illustrated in FIG. 9 includes only one set of feature point extraction conditions for each reference graphic. However, the target graphic table may include a plurality of feature point extraction conditions for a certain reference graphic. For example, the target graphic table has information of “(1) the center of gravity of the title and (2) two points far from the title among the vertices of the text” as the feature point extraction conditions corresponding to the reference graphic “golden triangle”. May be.

  According to the target graphic table illustrated in FIG. 9, a plurality of feature point extraction conditions are applied to a certain object. For example, feature point extraction conditions corresponding to three reference figures of a golden triangle, a golden rectangle, and a golden pentagon are applied to an object of category “title”. However, only a single feature point extraction condition may be applied to an object.

  The conditions for selecting an object from which feature points are extracted are not limited to those using the object category. Attribute information other than the category may be used as a condition for selecting an object from which feature points are extracted. In addition, when there are a plurality of objects that satisfy the condition, the objects to be processed may be specified one by one in order.

  The method of forming the target graphic using the feature points is not limited to that described in the embodiment and each modification. For example, among the polygons having (1) all feature points inside or on the boundary line, and (2) a boundary line parallel to a predetermined direction (for example, the vertical and horizontal directions of the layout area), (3) The one with the smallest area may be used as the target graphic.

  The method for calculating the degree of coincidence is not limited to that described in the embodiment and each modification. For example, in the reference graphic and the target graphic, the degree of coincidence may be calculated according to the ratio of the side length of the polygon, the angle of the vertex, and the like.

  The points used as the feature points are not limited to those described in the embodiment and each modification. For example, (1) vertex or end point of object boundary line or circumscribed polygon, (2) point dividing between two vertices or end points into a predetermined ratio (1: 1, golden ratio, etc.), (3 The center of gravity of the object and (4) the end point of the center line of the object may be extracted as feature points.

  The attribute information possessed by each object is not limited to that described in the above embodiment or modification. For example, the following may be used as attributes. (1) Object type (“text”, “image”, etc.), (2) Object category (“title”, “subtitle”, “body”, “main image”, “subimage”, etc.), (3) ) Font size, (4) Font type (“Mincho”, “Gothic”, etc.), (5) Font style (“Standard”, “Bold”, “Italic”, etc.), (6) Object size ( Area, number of characters, number of pixels, etc.), (7) object priority (“high”, “medium”, “low”, index, etc.), (8) image content (“person”, “landscape”, “ Mountain "," flower ", etc.). Each object need not have all the attribute information exemplified above.

  Each object may not have attribute information. The attribute of the object may be defined by data different from the object such as layout information. Alternatively, the attribute of the object may be determined in advance.

  The types of data, information, and parameters stored in the HDD 150 in the above-described embodiments and modifications may be stored in a device other than the HDD 150. For example, the design rule may be stored in a device other than the document evaluation device 100. In this case, the document evaluation apparatus 100 acquires a design rule from another apparatus through communication or direct connection via a network. In this case, the document evaluation apparatus 100 does not need to store design rules in advance. Alternatively, data, information and parameter classes may be entered by the user.

  The types of data, information, and parameters that are “predetermined” in the above-described embodiments and modifications may be determined according to a user instruction. Alternatively, these types of data, information and parameters may be determined by CPU 110 according to a predetermined algorithm.

  In the above-described embodiment and modification, the document evaluation program is stored in the HDD 150. However, the document evaluation program may be provided by a storage medium such as a CD-ROM (Compact Disk Read Only Memory).

It is a figure which shows the function structure of the document evaluation apparatus 100 which concerns on one Embodiment. 2 is a diagram illustrating a hardware configuration of a document evaluation apparatus 100. FIG. 4 is a flowchart showing the operation of the document evaluation apparatus 100. It is a figure which illustrates the document acquired. It is a flowchart which shows the detail of an evaluation value calculation process. It is a flowchart which shows the detail of a coincidence degree calculation process. It is a figure which illustrates the document used as the object of evaluation. 10 is a flowchart showing details of evaluation value calculation processing according to Modification 1; It is a figure which illustrates an object figure table. It is a figure which illustrates an object figure. It is a figure which illustrates an object figure. It is a figure which illustrates an object figure. It is a figure explaining the coincidence degree calculation method which concerns on the modification 2. FIG. It is a figure explaining the coincidence degree calculation method which concerns on the modification 3. FIG.

Explanation of symbols

DESCRIPTION OF SYMBOLS 100 ... Document evaluation apparatus, 101 ... Object acquisition part, 102 ... Reference | standard figure memory | storage part, 103 ... Matching degree calculation part, 104 ... Evaluation part, 110 ... CPU, 120 ... ROM, 130 ... RAM, 140 ... I / F, 150 ... HDD, 160 ... Keyboard / mouse, 170 ... Display, 180 ... Network IF, 190 ... Bus

Claims (9)

Object acquisition means for acquiring the position of an object included in a document to be evaluated;
A degree of coincidence calculating means for calculating a degree of coincidence between a target figure which is a figure formed by a feature point determined by the position of the object obtained by the object obtaining means and a predetermined reference figure;
A document evaluation apparatus comprising: evaluation means for evaluating the document based on the degree of coincidence calculated by the degree of coincidence calculation means.   The document evaluation apparatus according to claim 1, wherein a side of the reference graphic is a golden dividing line of a layout area that is an area in which an object is arranged in the document. The object acquisition means acquires the size or shape in addition to the position of the object,
The document evaluation apparatus according to claim 2, wherein at least one of the two reference lines is determined based on the position, size, or shape of the object acquired by the object acquisition unit. The document includes a plurality of objects;
The document evaluation apparatus according to claim 1, wherein the target graphic is a graphic formed by a plurality of feature points determined by positions, sizes, or shapes of the plurality of objects. The document evaluation apparatus according to claim 4, wherein the target graphic is a golden triangle, a golden rectangle, or a golden pentagon. The document includes a plurality of objects;
Each of the plurality of objects has attribute information indicating its attribute,
Storage means for storing a plurality of data sets that associate the shape of the reference graphic and the feature point extraction conditions;
The coincidence calculation means calculates a plurality of coincidences for a plurality of sets of reference figures and target figures corresponding to a plurality of data sets stored in the storage means,
The document evaluation apparatus according to claim 5, wherein the evaluation unit evaluates the document based on the plurality of matching degrees. The data set includes a weighting factor corresponding to each reference graphic;
The document evaluation apparatus according to claim 6, wherein the evaluation unit evaluates the document based on a result of a weighting operation that multiplies the degree of coincidence with each reference graphic by a weighting coefficient included in the data set. Computer equipment,
Obtaining a position of an object included in a document to be evaluated;
Calculating a degree of coincidence between a figure formed by a feature point determined by the position of the acquired object and a predetermined reference figure;
And a step of evaluating the document based on the calculated degree of coincidence. Computer equipment,
Obtaining a position of an object included in a document to be evaluated;
Calculating a degree of coincidence between a figure formed by a feature point determined by the position of the acquired object and a predetermined reference figure;
A storage medium storing a program for executing the step of evaluating the document based on the calculated degree of coincidence.

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