Document evaluation apparatus, method, and program, and document evaluation system

Abstract

To provide a document evaluation apparatus, method, program, and document evaluation system capable of reducing the load and improving the efficiency of evaluation processing for multiple evaluation items related to the readability of a document.SOLUTION: A document evaluation apparatus includes: a document data acquisition unit 11 that acquires document data including at least an object of a character string; a preprocessing unit 12 that performs preprocessing on the document data acquired by the document data acquisition unit; an information amount evaluation unit 13 that evaluates an information amount of the document data on the basis of the preprocessed document data; a character evaluation unit 14 that evaluates the readability of the character strings on the basis of the preprocessed document data; and a color evaluation unit 15 that evaluates the relationship between adjacent colors in the document data on the basis of the preprocessed document data.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present invention relates to a document data evaluation device, method, program, and document evaluation system for evaluating the understandability of document data. [Background technology]

[0002] The ease of understanding of information in a document is a vague concept. It is difficult to objectively evaluate the ease of understanding of information in a document because the criteria for judgment vary depending on the physical and ability characteristics, knowledge and skills, experience, interests, purpose and usage of the document, preferences, etc. of the reader of the document.

[0003] Therefore, Non-Patent Document 1 classifies "ease of understanding information" into nine items from the perspective of information design for human communication, and defines evaluation criteria for each. The nine items here are "amount of information," "task," "text (ease of understanding the meaning of the sentence)," "layout," "typography (ease of reading the characters)," "color design," "marks and diagrams," "fill-in (input) fields," and "problems in use."

[0004] Furthermore, Patent Document 1 proposes an evaluation method for the nine items shown in Non-Patent Document 1. [Prior art documents] [Non-patent literature]

[0005] [Non-Patent Document 1] Universal Communication Design Association, "9 points for clarity", Internet<URL:https: / / ucda.jp / ninsho_mokuteki / kijun.html#01> [Patent documents]

[0006] [Patent Document 1] JP 2011-020387 A Summary of the Invention [Problem to be solved by the invention]

[0007] However, the evaluations based on Non-Patent Document 1 and Patent Document 1 must be performed by experts with knowledge and evaluation skills in information design. Even among experts, there are individual differences in knowledge and skills, so it is not possible to completely eliminate the personal nature of the evaluation.

[0008] In addition, in Patent Document 1, dedicated evaluation methods, judgment tools, devices, etc. are used for multiple types of evaluation items. Therefore, in actual evaluation, it takes time and effort to use these evaluation methods, judgment tools, and devices. In addition, it is necessary to become familiar with how to use the evaluation methods, judgment tools, devices, etc.

[0009] Therefore, there is a demand for a device that can automatically evaluate multiple evaluation items in a batch. However, a document to be evaluated contains various objects in addition to objects containing character strings, and when a process of evaluating multiple evaluation items in a batch is performed on such a document, the load of the calculation process is large, and a calculation device with high processing power is required, and it takes a long time to obtain the evaluation result.

[0010] In addition, some file formats such as PDF have complex structures, so if coordinate conversion processes such as object rotation are performed for each evaluation item due to settings such as page rotation and page size for each page, there is a problem that unnecessary load is placed on the system.

[0011] In view of the above circumstances, the present invention aims to provide a document evaluation device, method, program, and document evaluation system that can reduce the burden of evaluation processing of multiple evaluation items related to the understandability of a document and improve efficiency. [Means for solving the problem]

[0012] The document evaluation device of the present invention comprises a document data acquisition unit that acquires document data including at least character string objects, a pre-processing unit that performs pre-processing on the document data acquired by the document data acquisition unit, an information amount evaluation unit that evaluates the information amount of the document data based on the pre-processed document data, a character evaluation unit that evaluates the readability of character strings based on the pre-processed document data, and a color evaluation unit that evaluates the relationship between adjacent colors in the document data based on the pre-processed document data. Effect of the Invention

[0013] According to the document evaluation device of the present invention, preprocessing is performed on document data, and then the amount of information in the document data, the readability of character strings, and the relationship between adjacent colors are evaluated based on the preprocessed document data, thereby reducing the load of evaluation processing for multiple evaluation items related to the understandability of a document and improving efficiency. [Brief description of the drawings]

[0014] [Figure 1] FIG. 1 is a block diagram showing a schematic configuration of a document evaluation system using an embodiment of a document evaluation device of the present invention. [Diagram 2] A diagram showing an example of adjacent objects, RGB values ​​of the colors of each object, and an example of a color list of adjacent colors. [Diagram 3] A diagram showing an example of the display of the evaluation results of the amount of information [Figure 4] A diagram showing an example of the typography evaluation results [Diagram 5] A diagram showing an example of the display of the evaluation results of a color design [Figure 6] FIG. 13 is a diagram showing an example of a display image selection screen. [Figure 7] FIG. 2 is a diagram for explaining the process flow of the document evaluation system shown in FIG. 1; [Figure 8] A diagram showing an example of a Japanese font and an example of a Western font. [Figure 9] An illustration of the procedure for deciding on a color change proposal [Figure 10] FIG. 1 is a diagram for explaining that there may be multiple colors that have the smallest color difference with respect to the color to be changed; DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0015] A document evaluation system using an embodiment of the document evaluation device of the present invention will be described in detail below with reference to the drawings. Fig. 1 is a block diagram showing a schematic configuration of a document evaluation system 1 of the present embodiment.

[0016] 1, the document evaluation system 1 of the present embodiment includes a document evaluation device 10 and a terminal device 20. The document evaluation device 10 and the terminal device 20 are connected via a wired or wireless communication line such as the Internet, and are configured to be able to communicate with each other.

[0017] The document evaluation device 10 acquires document data output from the terminal device 20 and evaluates the understandability of the document data. The document evaluation device 10 of this embodiment collectively evaluates three evaluation items of the document data, namely, "information amount," "typography (readability of characters)," and "color design," as evaluation items for the understandability of the document data, and outputs the evaluation result to the terminal device 20 for display.

[0018] Specifically, the document evaluation device 10 includes a document data acquisition unit 11 , a preprocessing unit 12 , an information amount evaluation unit 13 , a character evaluation unit 14 , a color evaluation unit 15 and an evaluation result output unit 16 .

[0019] The document data acquisition unit 11 acquires document data output from the terminal device 20. The document data is document data including at least a character string object, and may include vector graphic objects and bitmap image objects in addition to the character string object. As the document data, for example, document data in a Portable Document Format (PDF) format is output from the terminal device 20 and acquired by the document data acquisition unit 11.

[0020] The preprocessing unit 12 performs preprocessing on the document data acquired by the document data acquisition unit 11. In this embodiment, the preprocessing unit 12 performs a process of removing objects that are not subject to evaluation from the document data as preprocessing. Objects that are not subject to evaluation are objects that are excluded from the targets of the three evaluation items described above.

[0021] Examples of objects that are not subject to evaluation include transparent objects, objects hidden behind, and objects within the scope of trimming. These objects are visible to the creator of document data when the data is created on the terminal device 20, but are not visible when the created document data is distributed to a person other than the creator and displayed, for example, by viewing software (such as Acrobat Reader). In other words, these objects are visible to the creator of the document data, but are not visible to viewers of the document data after distribution.

[0022] Transparent objects include, for example, watermark character objects that are intentionally made transparent and inserted by the creator, and objects that are intentionally made transparent and inserted by the creator during the process of creating document data and that the creator forgot to delete when finally outputting the document data from the terminal device 20. However, the objects are not limited to these, and other transparent objects may also be deleted.

[0023] An object hidden behind another object is, for example, an object that is hidden behind a vector graphic object and cannot be seen.

[0024] An object within the scope of trimming is an object that exists within a range to which trimming has been applied, for example, by a trimming function of PDF editing software, during the process of creating document data in the terminal device 20. Objects within the scope of trimming are hidden when the document data is displayed or printed. As a preprocessing step, the preprocessing unit 12 also performs a process of extracting metadata set in the PDF document data. The metadata is data related to pages included in the document data, and is data indicating, for example, page rotation information, page information, and page size information. The metadata is used when converting coordinates indicating the position of a warning target, which will be described later, and when displaying a report of the evaluation results. In this embodiment, the metadata is extracted before generating intermediate data, which will be described later, so that the rotation process is not performed when generating the intermediate data, and the rotation process is performed thereafter using the metadata as necessary, so that the load of the rotation process can be reduced and efficiency can be improved.

[0025] Furthermore, the preprocessing unit 12 performs preprocessing for removing objects not to be evaluated and preprocessing for extracting metadata as described above, and then performs intermediate data generation processing for generating intermediate data based on the preprocessed document data. The intermediate data generation processing is processing for generating intermediate data suitable for evaluation of the three evaluation items described above from the preprocessed document data.

[0026] Specifically, the preprocessing unit 12 generates bitmap image data and object information data as intermediate data.

[0027] The bitmap image data is data generated by performing RIP (Raster Image Processor) processing on preprocessed document data. The bitmap image data is used when evaluating the amount of information in the information amount evaluation unit 13, or when displaying a color-converted bitmap image in a color appearance simulation, which will be described later. When generating a bitmap image to be used for evaluating the amount of information as the bitmap image data, the preprocessing unit 12 deletes graphic and photo objects that are not related to the evaluation of the amount of information in the document, and then generates the bitmap image data for evaluating the amount of information.

[0028] The object information data includes information such as the type of object, coordinates indicating the position of the object, the color of the object, and the font, size (point number), and line spacing of the character string included in the object. The object information data is used when the character evaluation unit 14 evaluates typography and the color evaluation unit 15 evaluates color design.

[0029] In this embodiment, as described above, the three evaluation items of the document data, namely, “information volume,” “typography,” and “color design,” are evaluated using intermediate data generated based on the preprocessed document data in the preprocessing unit 12.

[0030] The information amount evaluation unit 13 evaluates the information amount of the document data. In the present embodiment, the information amount evaluation unit 13 first performs edge detection processing on the bitmap image data for evaluating the amount of information generated in the intermediate data generation processing. Then, the information amount evaluation unit 13 performs binarization processing on the bitmap image data that has been subjected to the edge detection processing, and evaluates the information amount using the black and white bitmap image data. Specifically, the information amount evaluation unit 13 counts the number of black dots and the total number of dots for the black and white bitmap image data for each page of the document data, and calculates the black dot ratio. The black dot ratio is the ratio of the number of black dots to the total number of dots included in one page. Then, the information amount evaluation unit 13 evaluates whether the black dot ratio is less than a reference value (for example, 19%), and if it is less than the reference value, evaluates that it is not a target for warning, and if it is equal to or greater than the reference value, evaluates that it is a target for warning. This is because if the black dot ratio is equal to or greater than the reference value, the amount of information included in one page is too much, making it difficult to understand.

[0031] Moreover, the information amount evaluation unit 13 counts the number of white dots in addition to the above-mentioned black dot ratio, and calculates the white dot ratio.

[0032] The character evaluation unit 14 evaluates the typography of the document data. The character evaluation unit 14 of this embodiment evaluates the typography by using the object information data generated in the intermediate data generation process as described above.

[0033] Specifically, the character evaluation unit 14 evaluates whether the size (point number) of characters included on each page of the document data is equal to or larger than a preset point threshold (e.g., 8 points) based on the object information data. If the character size is equal to or larger than the point threshold, the character evaluation unit 14 evaluates the character size as not being subject to a warning, and if the character size is less than the point threshold, the character evaluation unit 14 evaluates the character size as being subject to a warning. This is because if the character size is less than the point threshold, the character is too small and difficult to read.

[0034] The character evaluation unit 14 also evaluates whether the line spacing of characters included on each page of the document data is equal to or greater than a preset line spacing threshold (for example, 1.5 lines). The line spacing is the arrangement interval of each line, which is the sum of the character height and the gap between each line.

[0035] The character evaluation unit 14 evaluates characters as not being subject to a warning if the line spacing is equal to or greater than the line spacing threshold, and evaluates characters as being subject to a warning if the line spacing is less than the line spacing threshold. This is because characters that are less than the line spacing threshold are perceived as being too narrow and difficult to read.

[0036] Furthermore, the character evaluation unit 14 evaluates whether the number of characters included in each line of each page of the document data is within a preset character count threshold (for example, 45 characters). If the number of characters in each line is within the character count threshold, the character evaluation unit 14 evaluates it as not being subject to a warning, and if the number of characters in each line exceeds the character count threshold, it evaluates it as being subject to a warning. This is because if the number of characters in one line exceeds the character count threshold, the number of characters is too large and it is difficult to read.

[0037] Furthermore, the character evaluation unit 14 evaluates whether each character included in the document data is deformed. Specifically, the character evaluation unit 14 evaluates whether the value of the horizontal ratio, which is one of the font information of each character included in the document data, exceeds a certain range. In the PDF document data of this embodiment, the above-mentioned horizontal ratio is set for each character. If there is no deformation in the character, the horizontal ratio is 100%, and if the character is stretched horizontally, the value is greater than 100%. In this embodiment, this horizontal ratio is extracted from the character object, and if it is within a certain range (for example, 100%±25%), it is evaluated as not being subject to a warning, and if it is outside the certain range, it is evaluated as being subject to a warning. This is because if a character is deformed, it is difficult to read.

[0038] The character evaluation unit 14 may perform the above-mentioned evaluation process on a line-by-line basis.

[0039] The color evaluation unit 15 evaluates the color design of the document data. Specifically, the color evaluation unit 15 compares the colors of all adjacent objects for each page of the document data and evaluates whether the colors are difficult to distinguish. In addition, when one object contains multiple colors, the color evaluation unit 15 divides the object into separate colors, compares the colors of adjacent dots, and evaluates whether the colors are difficult to distinguish.

[0040] The color evaluation unit 15 evaluates whether a color is difficult to distinguish based on whether the brightness difference between adjacent colors is equal to or greater than a preset brightness threshold. When the brightness difference between adjacent colors is equal to or greater than the preset brightness threshold, the color evaluation unit 15 evaluates the color as not requiring a warning, and when the brightness difference between adjacent colors is less than the preset brightness threshold, the color evaluation unit 15 evaluates the color as requiring a warning.

[0041] Furthermore, when evaluating a color design as described above, the color evaluation unit 15 may create a color scheme list of adjacent objects and use the color scheme list to evaluate the color design.

[0042] Fig. 2A is a diagram showing an example of adjacent objects I to IV, Fig. 2B is a diagram showing RGB values ​​of each color of objects I to IV shown in Fig. 2A, and Fig. 2C is a diagram showing RGB values ​​of all color combinations of adjacent objects I to IV. The color evaluation unit 15 may evaluate the color design using a color scheme list as shown in Fig. 2C.

[0043] In addition to color evaluation for general color vision, which uses the colors of the original document data as is, the color evaluation unit 15 also performs color evaluation for P-type color vision (deuteranopia), color evaluation for D-type color vision (deuteranopia), and color evaluation for the elderly.

[0044] When performing color evaluation for protanopia (deuteranopia), the color evaluation unit 15 performs color conversion processing for protanopia on the color of each object, and performs the above-mentioned color evaluation using the color after the color conversion. When performing color evaluation for deuteranopia (deuteranopia), the color evaluation unit 15 performs color conversion processing for deuteranopia on the color of each object, and performs the above-mentioned color evaluation using the color after the color conversion. When performing color evaluation for elderly people, the color evaluation unit 15 performs color conversion processing for elderly people on the color of each object, and performs the above-mentioned color evaluation using the color after the color conversion.

[0045] The color conversion process for P-type color vision, the color conversion process for D-type color vision, and the color conversion process for the elderly are each performed using a color conversion table that is set in advance.

[0046] The evaluation result output unit 16 outputs the evaluation results of the information amount evaluation unit 13, the evaluation results of the character evaluation unit 14, and the evaluation results of the color evaluation unit 15 to the terminal device 20 for display.

[0047] Fig. 3 is a diagram showing an example of the display of the evaluation result of the information amount evaluation unit 13. As shown in Fig. 3, the evaluation result output unit 16 displays an evaluation target page display field C1 and a dot number display field C2 as the evaluation result of the information amount. The evaluation target page display field C1 displays the page of the document data to be evaluated, and the dot number display field C2 displays the black dot ratio, white dot ratio, black dot count, white dot count, and total dot count of the page displayed in the evaluation target page display field C1. Then, when the black dot ratio is equal to or greater than the reference value, a warning message saying "The information amount of this page exceeds the reference value" is displayed in the dot number display field C2, as shown in Fig. 3.

[0048] In addition, when "Display report" displayed in the dot count display column C2 is selected, the evaluation result output unit 16 creates a report indicating whether the evaluation result of the amount of information for each page of the document data is subject to no warning or to a warning, and outputs the report to the terminal device 20 for display.

[0049] Fig. 4 is a diagram showing an example of the display of the evaluation results of the character evaluation unit 14. As shown in Fig. 4, the evaluation result output unit 16 displays a warning portion display field T1 and a warning portion count display field T2 as the typography evaluation results. Each page of the document data is displayed in the warning portion display field T1, and portions evaluated as warning targets are highlighted. Methods of highlighting include, for example, surrounding the character strings that are to be warned, underlining the warning target, or attaching an icon to the warning target.

[0050] The warning area number display field T2 displays the number of areas where the character size is less than the point threshold and therefore is evaluated as requiring a warning, the number of lines where the line spacing is less than the line spacing threshold and therefore is evaluated as requiring a warning, the number of lines where the number of characters in a line exceeds the character count threshold and therefore is evaluated as requiring a warning, and the number of areas where character deformation is present.

[0051] In addition, when "Display report" displayed in the warning item number display field T2 is selected, the evaluation result output unit 16 creates a report indicating whether the evaluation results of typography (character size, line spacing, number of characters per line, character deformation) for each page of the document data are non-warning items or warning items, and outputs it to the terminal device 20 for display.

[0052] FIG. 5 is a diagram showing an example of the display of the evaluation results of the color evaluation unit 15. As shown in FIG. 5, the evaluation result output unit 16 displays a warning target portion display field S1 and a warning target portion number display field S2 as the evaluation results of the color design. In the warning target portion display field S1, each page of the document data is displayed, and the portions evaluated as warning targets are highlighted. In the example shown in FIG. 5, a mark with an exclamation mark (!) surrounded by a square is displayed in the portion evaluated as warning targets. In the warning target portion number display field S2, the number of portions evaluated as warning targets, that is, the number of portions where the brightness difference of adjacent colors is less than the brightness threshold, is displayed, and a warning message saying "The color scheme is difficult to distinguish" is displayed.

[0053] Furthermore, when a predetermined "!" is selected in the warning target portion display field S1, the evaluation result output unit 16 displays the RGB values ​​of the original adjacent colors (first color and second color) of the selected portion and the RGB values ​​of the adjacent colors after the change. The RGB values ​​of the adjacent colors after the change are a color combination whose brightness difference is equal to or exceeds a brightness threshold value, and are a color combination recommended as a change from the original. The recommended color combination is calculated based on the RGB values ​​of the original colors, and is calculated using a preset table or function, etc.

[0054] In addition, when "Display report" displayed in the warning area number display field S2 is selected, the evaluation result output unit 16 creates a report indicating whether the color evaluation result for each page of the document data is a non-warning area or a warning area, and outputs it to the terminal device 20 for display.

[0055] Furthermore, the evaluation result output unit 16 can output and display the document data of the original color, the document data after color conversion for P-type color vision, the document data after color conversion for D-type color vision, and the document data after color conversion for the elderly on the terminal device 20. The evaluation result output unit 16 can display a display image selection screen as shown in Fig. 6, for example, and display the document data of the color selected (checkbox checked) on the display image selection screen on the terminal device 20. At this time, if document data of multiple colors is selected, the document data of each color is displayed on the terminal device 20. This makes it possible to compare how the colors of the document data appear.

[0056] The document evaluation device 10 is composed of a computer and includes a CPU (Central Processing Unit), semiconductor memories such as a ROM (Read Only Memory) and a RAM (Random access memory), storage such as a hard disk, and a communication I / F. An embodiment of the document evaluation program of the present invention is installed in the storage of the document evaluation device 10, and the above-mentioned components of the document evaluation device 10 operate when the document evaluation program is executed by the CPU.

[0057] In this embodiment, the functions of each part of the document evaluation device 10 are realized by a document evaluation program, but this is not limited to the above, and some or all of the functions or controls may be realized by hardware such as an ASIC (Application Specific Integrated Circuit), an FPGA (Field-Programmable Gate Array), or other electrical circuits.

[0058] As described above, the terminal device 20 outputs the document data in PDF format to the document evaluation device 10, and displays the evaluation results of the document data in terms of "information amount," "typography," and "color design."

[0059] The terminal device 20 is configured from a computer, and includes a CPU, semiconductor memories such as ROM and RAM, storage such as a hard disk, and a communication I / F.

[0060] A document evaluation application is installed in the storage of the terminal device 20, and the above-mentioned functions of the terminal device 20 are realized by this document evaluation application working in conjunction with the document evaluation program of the document evaluation device 10.

[0061] The terminal device 20 includes a control unit 21, an input unit 22, and a display unit 23. The control unit 21 includes the above-mentioned CPU, semiconductor memory, storage, and a communication I / F, and controls the terminal device 20 as a whole.

[0062] The input unit 22 includes input devices such as a mouse and a keyboard, and receives various inputs from the user. The display unit 23 includes a display device such as a liquid crystal display, and displays the evaluation results in the document evaluation device 10 described above.

[0063] Next, the flow of processing in the document evaluation system 1 of this embodiment will be described with reference to FIG.

[0064] First, in the terminal device 20, document data to be evaluated is created, and the document data to be evaluated is output to the document evaluation device 10 (S10, PDF upload).

[0065] Next, pre-processing is performed to remove objects that are not to be evaluated from the document data (S12). The document data D0 shown in Fig. 7 includes a transparent object OB1 and an object OB2 hidden behind the object, and the range indicated by the dotted line rectangle is specified as the range to which trimming is applied, and the range to which trimming is applied includes protruding objects OB3, OB4, and OB5. Therefore, in the case of the document data D, the transparent object OB1, the object OB2 hidden behind the object, the protruding objects OB3 and OB4, and a part of the protruding object OB5 are removed.

[0066] Next, after objects not to be evaluated are removed from the document data, intermediate data generation processing is performed on the preprocessed document data D1 to generate intermediate data (bitmap image data, object information data, and metadata) (S14).

[0067] Then, as shown in FIG. 7, an information amount evaluation process (S16), a typography evaluation process (S18), a color design evaluation process (S20), and a color appearance simulation process (S22) are carried out in parallel.

[0068] In the information amount evaluation process, as described above, the bitmap image data for information amount evaluation generated in the intermediate data generation process is subjected to edge detection processing and then binarization processing to generate black and white bitmap image data. Then, the information amount of each page is calculated based on the black and white bitmap image data of each page, and the information amount is evaluated. Then, a report of the information amount is displayed. When the report is displayed, the bitmap image data generated in the intermediate data generation process is displayed.

[0069] In the typography evaluation process, the size of characters, the spacing between characters, the number of characters in each line, and the presence or absence of deformed characters are evaluated based on the object information data generated in the intermediate data generation process as described above. Then, a list of the number of warning objects on each page and the coordinates of the positions of the warning objects is obtained.

[0070] Here, for example, when creating original document data, page rotation (e.g., 90° rotation, 180° rotation, etc.) may be set for the page. In this case, the page appears as it is after the page rotation, but the document data of the page itself is not rotated, and the above-mentioned typography evaluation process is also performed using the document data before the page rotation. Therefore, the coordinate list of the position of the above-mentioned warning target is the coordinate list before the page rotation, so a coordinate conversion process is performed on the coordinate list here to make it the same coordinate system as the page after the page rotation. This coordinate conversion process is performed based on the number of pages, page size, and page rotation information included in the metadata.

[0071] Then, as the evaluation result, the number of warning targets for each page is displayed, and the positions of the warning targets are highlighted based on the list of coordinates after the coordinate conversion. A report of the typography evaluation is then displayed. When the report is displayed, the bitmap image data generated in the intermediate data generation process is displayed.

[0072] In the color design evaluation process, it is evaluated whether adjacent colors are difficult to distinguish based on the object information data generated in the intermediate data generation process as described above. Then, a list of coordinates of positions of warning targets on each page is obtained.

[0073] Here, in the color design evaluation process, as in the typography evaluation process, if page rotation is set for the pages of the original document data, a coordinate conversion process is performed on the above coordinate list to make it the same coordinate system as the page after the page rotation. This coordinate conversion process is performed based on the number of pages, page size, and page rotation information included in the metadata.

[0074] Then, as the evaluation result, the number of warning targets for each page is displayed, and the positions of the warning targets are displayed with a "!" mark based on the list of coordinates after the coordinate conversion. A report of the color design evaluation is then displayed. When the report is displayed, the bitmap image data generated in the intermediate data generation process is displayed.

[0075] In the color appearance simulation process, color conversion processes for P-type color vision, D-type color vision, and elderly people are performed on the bitmap image data generated in the intermediate data generation process as described above, and color-converted bitmap image data is generated and displayed. Then, a report of the color-converted bitmap image data is displayed. When the report is displayed, the bitmap image data before color conversion generated in the intermediate data generation process is also displayed.

[0076] In the document evaluation system 1 of this embodiment, preprocessing is performed to remove objects that are not to be evaluated from the document data, and the document data is evaluated for its information volume, readability of character strings, and relationships between adjacent colors based on the preprocessed document data. This reduces the burden of evaluation processing for multiple evaluation items related to the understandability of a document and improves efficiency.

[0077] In addition, the document evaluation system 1 of this embodiment is equipped with an evaluation result output unit 16 that outputs the evaluation results of the information amount evaluation unit 13, the character evaluation unit 14, and the color evaluation unit 15, so that the user can instantly check the evaluation results on the terminal device 20.

[0078] Furthermore, in the document evaluation system 1 of this embodiment, since document data can include vector graphic objects and bitmap image objects, it is possible to evaluate various types of document data.

[0079] Furthermore, in the document evaluation system 1 of this embodiment, the document data can include font information of character strings, so that the presence or absence of deformation of characters can be evaluated using the font information in the typography evaluation process.

[0080] In addition, in the document evaluation system 1 of this embodiment, the evaluation result output unit 16 can output information indicating the location of the warning target in the document data as the evaluation result, so that the user can immediately grasp the location of the warning target in the document data.

[0081] Furthermore, in the document evaluation system 1 of this embodiment, when the document data contains page rotation information, the evaluation result output unit 16 can perform coordinate conversion processing according to the page rotation on the information indicating the position of the warning target in the document data, so that the position of the warning target can be displayed accurately.

[0082] Next, other embodiments of the character evaluation process in the character evaluation unit 14 will be described.

[0083] There are various types of fonts for document data, such as Japanese fonts and Latin fonts. In Japanese fonts, characters are arranged so that they fit between the bottom reference line and the top reference line in the vertical direction, regardless of whether they are full-width or half-width. However, in Latin fonts, there are characters that extend beyond the bottom reference line, such as "g" and "j".

[0084] Therefore, in the evaluation of line spacing in the character evaluation process, it is not preferable to use the same line spacing threshold for lines that contain only Japanese fonts and lines that contain Latin fonts. Therefore, different line spacing thresholds may be used for lines that do not contain Latin fonts and lines that contain Latin fonts. The process will be described in detail below.

[0085] First, the character evaluation unit 14 judges whether the characters included in the document data are subject to inspection or non-subject to inspection. Subject to inspection characters are characters whose meaning needs to be recognized by humans, and include both half-width and full-width characters in Japanese fonts (hiragana, katakana, kanji) and Western fonts (English, French, German, etc.). Non-subject to inspection characters include punctuation marks ("," "."," ","," "."), symbols (" / ," "@," "\"), and spaces.

[0086] The character evaluation unit 14 then judges whether the character that has been judged to be the target character is of a Roman typeface. The typeface may be judged to be Japanese or Roman based on the character code, or may be judged based on the type of font used.

[0087] Next, the character evaluation unit 14 judges whether or not each line included in the document data includes a character to be inspected that has been determined to be in a Latin typeface. Fig. 8A is a diagram showing an example of a Japanese typeface, and Fig. 8B is a diagram showing an example of a Latin typeface.

[0088] As shown in FIG. 8A, in a Japanese font, regardless of whether the character is full-width or half-width, the character is arranged so as to fit between a lower reference line L1 and an upper reference line L2 in the vertical direction.

[0089] On the other hand, as shown in Fig. 8B, in addition to the lower reference line L1 and the upper reference line L2, a descender line L3 indicating the position of the lowest point extending downward of the character and a mean line L4 that is a line passing through the head of the lowercase character are provided. Because the descender line L3 is provided in this way, some characters, such as "g" and "j", extend beyond the lower reference line L1 and are drawn to the descender line L3 below the lower reference line L1. Even if there is a Roman character, it is desirable to match the line spacing to Japanese characters, and therefore, in a text that contains a mixture of Japanese and Roman characters, the character height is high and the gap between each line is small, so the line spacing based on the character height is a small value.

[0090] Therefore, when evaluating the line spacing of a line determined not to include a Roman font, the character evaluation unit 14 uses a predetermined first line spacing threshold Th1 for the evaluation. Also, when evaluating the line spacing of a line determined to include a Roman font, the character evaluation unit 14 uses a second line spacing threshold Th2 smaller than the first line spacing threshold Th1 for the evaluation. In this way, by setting the second line spacing threshold Th2 to a value smaller than the first line spacing threshold Th1, in a text that contains a mixture of Japanese and Roman characters, it is possible to obtain line spacing that improves the readability of lines that include a Japanese font while keeping the line spacing between the next line the same value throughout the entire text.

[0091] Furthermore, when the character evaluation unit 14 evaluates the number of characters contained in one line, the count may be made excluding the above-mentioned non-test target characters.

[0092] By the way, if the number of characters per line is small and the line spacing is too wide, the text will not be able to form a coherent sentence. As mentioned above, the line spacing is the sum of the character height and the gap between each line, and is expressed as 1.5 lines (150%) based on the character height. In this way, the desired line spacing should be determined based on the character height and the number of characters per line.

[0093] Therefore, in the document evaluation system 1 of the above embodiment, the recommended line spacing for a character string may be determined based on the character size and number of characters in the direction perpendicular to the character arrangement direction in the character string of the document, or the character size and width of the character string. This makes it possible to determine an easy-to-read line spacing.

[0094] Specifically, if the number of characters in a line is 14 or less, the width is "character height x 1.5". That is, the recommended line spacing is determined to be 1.5 lines. Also, if the number of characters per line is 15 to 39, the recommended line spacing is determined to be "character height x (1.5 + (number of characters - 14) x 0.02)". In other words, if the number of characters per line is 15, the recommended line spacing is determined to be 1.52 lines, if it is 16, the recommended line spacing is determined to be 1.54 lines, ..., if it is 38, the recommended line spacing is determined to be 1.98 lines, and if it is 39, the recommended line spacing is determined to be 2.0 lines.

[0095] In addition, if the number of characters per line is 40 or more and 45 or less, the recommended line spacing is determined to be "character height x 2.0", or 2.0 lines.

[0096] The method for determining the recommended line spacing described above is merely an example, and the formula, maximum and minimum number of characters, etc. may be changed by user settings, for example. However, it is desirable to make the line spacing wider as the number of characters per line increases (the wider the width of one line) within a specified line spacing (for example, 1.5 lines to 2.0 lines).

[0097] Then, the above-mentioned recommended line spacing may be used to evaluate the line spacing of characters.

[0098] In addition, in the document evaluation system 1 of the above embodiment, the parts evaluated as objects to be warned in the document evaluation are highlighted. However, other methods of highlighting the parts include, for example, surrounding the objects to be warned, underlining the objects to be warned, or adding an icon to the objects to be warned.

[0099] When additional information such as the above-mentioned box lines, underlines, and icons is superimposed on document data, depending on the combination of the color of the document data to be evaluated and the color of the additional image, it may be difficult for the evaluator to distinguish between them.

[0100] Therefore, the evaluation result output unit 16 may adjust the color of the document data and the color of the additional information based on an external input (for example, input from the input unit 22 of the terminal device 20) so as to improve the readability of the document data to which the additional information has been added.

[0101] In addition, in the document evaluation system 1 of the above embodiment, if a document is evaluated as being subject to a warning in the color design evaluation process, a recommended post-change color combination (change proposal) is calculated and its RGB values ​​are displayed. Other embodiments of the method for determining this change proposal will be described below.

[0102] The evaluation result output unit 16 may determine, as a proposed change to the two-color combination, a combination in which at least one of the two colors of the color combination to be warned about is changed so that people with color vision deficiency (people with P-type color vision and people with D-type color vision) can distinguish between the two colors, and in which the degree of change in at least one of the two colors is minimized for people with normal color vision.

[0103] Specifically, the evaluation result output unit 16 first converts document data in the recognition color space of a person with normal color vision into image data in the recognition color space of a person with color vision deficiency. The conversion from document data in the recognition color space of a person with normal color vision to image data in the recognition color space of a person with color vision deficiency can be performed using a known method.

[0104] For example, the evaluation result output unit 16 converts the document data into document data in a linear sRGB color space by the following equations (1) to (3).

number

[0105] Here, Rdevice, Gdevice, and Bdevice in the formulas (1) to (3) are the R, G, and B values ​​in the document data, respectively. ) Rlinear, Glinear, and Blinear are the R, G, and B values ​​in the linear sRGB color space, respectively.

[0106] Next, the evaluation result output unit 16 converts the image data in the linear sRGB color space into document data in the LMS color space that is recognized by a person with normal color vision, using the following formula (4).

number

[0107] Next, the evaluation result output unit 16 converts the document data in the LMS color space recognized by a person with normal color vision into document data in the LMS color space recognized by a person with P-type color vision abnormality, using the following formula (5).

[0108] Furthermore, the evaluation result output unit 16 converts document data in the LMS color space recognized by a person with normal color vision into document data in the LMS color space recognized by a person with D-type color vision deficiency, using the following formula (6).

number

[0109] Then, the evaluation result output unit 16 converts the document data in the LMS color space recognized by a person with protanopia into image data in the RGB color space recognized by a person with protanopia. The evaluation result output unit 16 also converts the document data in the LMS color space recognized by a person with deuterium-type color vision into image data in the RGB color space recognized by a person with deuterium-type color vision. Here, the conversion from the LMS color space to the RGB color space can be performed using a known method.

[0110] Next, the evaluation result output unit 16 extracts combinations of two adjacent colors in the document data in the color space recognized by the color vision deficiency person (RGB color space recognized by the color vision deficiency person).

[0111] Specifically, the evaluation result output unit 16 searches for combinations of two overlapping objects of different colors in the document data in the recognition color space of the color vision deficiency person, using information indicating the position of each object. Then, the evaluation result output unit 16 extracts a combination of two colors in a combination of two adjacent or overlapping objects of different colors as a combination of two adjacent colors. Note that if an object contains multiple colors, each part is regarded as an object, and the combination of two colors is adjacent to each other.

[0112] Here, the evaluation result output unit 16 extracts combinations of two adjacent colors for each of the image data in the recognition color space of the person with P-type color vision deficiency and the document data in the recognition color space of the person with D-type color vision deficiency. Multiple combinations may be extracted for each document data.

[0113] Next, for each combination extracted as described above, the evaluation result output unit 16 judges whether or not the combination is one in which a person with color vision deficiency is likely to confuse two colors. Specifically, the evaluation result output unit 16 judges whether or not the combination is one in which a person with color vision deficiency is likely to confuse two colors based on the difference in lightness between the two colors recognized by the person with color vision deficiency.

[0114] For example, for each combination, the evaluation result output unit 16 converts the RGB values ​​of each of the two colors recognized by the color vision deficiency person into L*a*b* values. The conversion from RGB values ​​to L*a*b* values ​​can be performed using a known method.

[0115] Then, when the difference in L* value, which is the difference in lightness between the two colors, is equal to or less than a predetermined threshold, the evaluation result output unit 16 determines that the combination of the two colors is one that is likely to be confused by a person with color vision deficiency.

[0116] Here, the evaluation result output unit 16 determines whether or not each combination of document data in the recognition color space of a person with P-type color vision deficiency and document data in the recognition color space of a person with D-type color vision deficiency is a combination in which a person with color vision deficiency of the respective color vision type is likely to confuse two colors.

[0117] Next, for a combination that is determined to be likely to cause confusion between two colors by a person with color vision deficiency, the evaluation result output unit 16 determines a change plan for one of the colors so that the person with color vision deficiency can distinguish between the two colors and the degree of change to the color to be changed is minimized for people with normal color vision.

[0118] Here, we consider the combinations of two colors that are easily confused by color vision deficiencies, and the combinations that are easily confused by color vision deficiencies. The L*a*b* values ​​of the two colors to be recognized are [L1_n, a1_n, b1_n], [L2_n, Among these, the color of [L2_n, a2_n, b2_n] is the target for change. do.

[0119] In addition, the L*a*b* values ​​of the above two colors as perceived by a person with P-type color vision deficiency are [L1_ p, a1_p, b1_p], [L2_p, a2_p, b2_p]. The L*a*b* values ​​of the above two colors recognized by a person with D-type color vision deficiency are respectively [L1_d, a1_d, b1_d ],[L2_d,a2_d,b2_d].

[0120] The evaluation result output unit 16 obtains the L*a*b* values ​​[L3_n, a3_n, b3_n] of the color recognized by a person with normal color vision after the color to be changed, by solving a constrained optimization problem that minimizes the evaluation function J shown in the following equation (7).

number

[0121] Here, minJ(x)=f(x) is the vector x that minimizes the evaluation function J. This is a formula that expresses the optimization problem. Also, st expresses the constraints on the variables of the evaluation function J. represent.

[0122] The first line of equation (7) means to obtain the post-change color that has the smallest color difference from the pre-change color for a person with normal color vision.

[0123] In addition, const in formula (7) is a preset threshold value of the brightness difference at which a person with color vision deficiency can distinguish between two colors. In addition, L3_p and L3_d in formula (7) are the L* values ​​of the colors [L3_n, a3_n, b3_n] as recognized by a person with color vision deficiency with P type color vision and a person with color vision deficiency with D type color vision, respectively.

[0124] In addition, the condition in the bottom line of formula (7) is that the L*a*b* values ​​can be expressed in the RGB color space. This means that the color must correspond to the color specified in the specification.

[0125] When there are multiple solutions to the constrained optimization problem of equation (7), the evaluation result output unit 16 selects the color with the smallest difference in lightness from the color to be changed as the proposed change color. In other words, the evaluation result output unit 16 selects the color with the smallest |L2_n-L3_n| as the proposed change color.

[0126] A specific example of a method for solving the constrained optimization problem of equation (7) will be described.

[0127] First, the L*a*b* color space recognized by a person with normal color vision is quantized at a predetermined interval, and all L*a*b* values ​​are listed.

[0128] Next, each L*a*b* value in the above list recognized by a person with normal color vision is converted to an L*a*b* value recognized by a person with color vision deficiency of P type, and each converted L*a*b* value is stored in correspondence with each L*a*b* value recognized by a person with normal color vision. Also, each L*a*b* value in the above list recognized by a person with normal color vision is converted to an L*a*b* value recognized by a person with color vision deficiency of D type, and each converted L*a*b* value is stored in correspondence with each L*a*b* value recognized by a person with normal color vision. Attach and hold.

[0129] Here, the L*a*b* values ​​recognized by a person with normal color vision are compared with the L*a*b* values ​​recognized by a person with P-type color vision deficiency. Conversion to a*b* values, and conversion from L*a*b* values ​​recognized by a person with normal color vision to L*a*b* values ​​recognized by a person with D-type color vision deficiency can be performed using known techniques.

[0130] For example, the L*a*b* values ​​perceived by a person with normal color vision are compared to the L* values ​​perceived by a person with P-type color vision deficiency. When converting to a*b* values, first convert the L*a*b* values ​​recognized by a person with normal color vision into RGB values ​​recognized by a person with normal color vision. Then, convert the RGB values ​​recognized by a person with normal color vision into the colors recognized by a person with P-type color vision. The RGB values ​​recognized by the color vision deficiency patient are converted to RGB values ​​recognized by the color vision deficiency patient. This conversion can be performed using the method described above. Next, the RGB values ​​recognized by the color vision deficiency patient with P-type color vision are converted to L*a*b* values ​​recognized by the color vision deficiency patient with P-type color vision. Conversion between RGB values ​​and L*a*b* values ​​can be performed using a known method.

[0131] Conversion of the L*a*b* values ​​perceived by a person with normal color vision to the L*a*b* values ​​perceived by a person with D-type color vision deficiency can be performed in the same manner as the conversion to the L*a*b* values ​​perceived by a person with P-type color vision deficiency described above.

[0132] Next, each L*a*b* value recognized by a person with normal color vision, which corresponds to each L*a*b* value whose difference in lightness (L* value) with respect to [L1_p, a1_p, b1_p] in the list of L*a*b* values ​​recognized by a person with P color vision deficiency described above is equal to or less than const in formula (7), is deleted from the list of L*a*b* values ​​recognized by a person with normal color vision. Also, each L*a*b* value recognized by a person with normal color vision, which corresponds to each L*a*b* value whose difference in lightness (L* value) with respect to [L1_d, a1_d, b1_d] in the list of L*a*b* values ​​recognized by a person with D color vision deficiency described above is deleted from the list of L*a*b* values ​​recognized by a person with normal color vision.

[0133] As a result, the L*a*b* values ​​of multiple colors whose lightness difference with respect to the L*a*b* value [L1_n, a1_n, b1_n] of the color not to be changed is greater than const remains in the list of L*a*b* values ​​recognized by a person with normal color vision described above. In other words, as shown in Figure 9, multiple colors whose lightness difference with respect to the color not to be changed is greater than const are extracted from the L*a*b* color space recognized by a person with normal color vision.

[0134] Next, among the L*a*b* values ​​remaining in the list of L*a*b* values ​​recognized by a person with normal color vision, which are the L*a*b* values ​​of colors that can be expressed in the RGB color space, the L*a*b* value of the color to be changed on the a*b* plane [L2_n, a2_n, b2 _n] is selected.

[0135] As a result, from each color extracted as having a lightness difference greater than const with respect to the non-change color, a color that can be expressed in the RGB color space and has the smallest color difference from the change target color is extracted, as shown in Fig. 9. A color with the smallest color difference from the change target color means that the degree of color change from the change target color is the smallest for a person with normal color vision.

[0136] Here, as shown in Fig. 10, there may be multiple colors that have the smallest color difference (distance on the a*b* plane) from the color to be changed. If there are multiple colors that have the smallest color difference from the color to be changed, that is, if there are multiple solutions to the constrained optimization problem of equation (7), the color that has the smallest lightness difference from the color to be changed is selected as the color of the proposed change.

[0137] The evaluation result output unit 16 determines a change proposal for one of the colors by solving the constrained optimization problem of equation (7) as described above for all combinations in which at least either a person with P-type color vision deficiency or a person with D-type color vision deficiency is likely to confuse two colors.

[0138] After the proposed change is determined, the evaluation result output unit 16 transmits the proposed change to the terminal device 20. This makes it possible for the terminal device 20 to display on the display unit 23 the proposed change to one of the two colors in a combination that is likely to be confused by a person with color vision deficiency, and to notify the user of the proposed change.

[0139] The present invention is not limited to the above-described embodiment, and the components can be modified and embodied in the implementation stage without departing from the gist of the invention. In addition, various inventions can be formed by appropriately combining the multiple components disclosed in the above-described embodiment. For example, all the components shown in the embodiment can be appropriately combined. Of course, various modifications and applications are possible without departing from the spirit of the invention.

[0140] The present invention further discloses the following supplementary notes.

[0141] (Appendix 1) The document evaluation device of the present invention comprises a document data acquisition unit that acquires document data including at least character string objects, a pre-processing unit that performs pre-processing on the document data acquired by the document data acquisition unit, an information amount evaluation unit that evaluates the information amount of the document data based on the pre-processed document data, a character evaluation unit that evaluates the readability of character strings based on the pre-processed document data, and a color evaluation unit that evaluates the relationship between adjacent colors in the document data based on the pre-processed document data.

[0142] (Appendix 2) In the document evaluation device according to supplementary note 1, the preprocessing unit can perform a process of removing objects that are not to be evaluated from the document data as the preprocessing.

[0143] (Appendix 3) The document evaluation device according to claim 1 or 2 may further include an evaluation result output unit that outputs the evaluation results of the information amount evaluation unit, the character evaluation unit, and the color evaluation unit.

[0144] (Appendix 4) In the document evaluation device according to any one of Supplementary Notes 1 to 3, the document data can include vector graphic objects and bitmap image objects.

[0145] (Appendix 5) In the document evaluation device according to any one of Supplementary Notes 1 to 4, the document data can include font information of a character string.

[0146] (Appendix 6) In the document evaluation device according to any one of Supplementary Notes 1 to 5, the evaluation result output unit can output information indicating a position of a warning target in the document data as the evaluation result.

[0147] (Appendix 7) In a document evaluation device described in any of Appendices 1 to 6, when the document data includes page rotation information, the evaluation result output unit can perform coordinate conversion processing corresponding to the page rotation on information indicating the position of a warning target in the document data.

[0148] (Appendix 8) The document evaluation system of the present invention includes a document evaluation device according to any one of claims 1 to 7, and a terminal device that displays an evaluation result in the character evaluation device.

[0149] (Appendix 9) The document evaluation method of the present invention acquires document data including at least a character string object, performs preprocessing on the acquired document data, evaluates the information volume of the document data based on the preprocessed document data, evaluates the readability of the character string based on the preprocessed document data, and evaluates the relationship between adjacent colors in the document data based on the preprocessed document data.

[0150] (Appendix 10) The document evaluation program of the present invention causes a computer to execute the steps of acquiring document data including at least character string objects, performing preprocessing on the acquired document data, evaluating the information volume of the document data based on the preprocessed document data, evaluating the readability of the character string based on the preprocessed document data, and evaluating the relationship between adjacent colors in the document data based on the preprocessed document data. [Explanation of symbols]

[0151] 1 Document Evaluation System 10 Document evaluation device 11 Document Data Acquisition Unit 12 Pretreatment section 13 Information Quantity Evaluation Unit 14 Character Evaluation Section 15 Color Evaluation Department 16 Evaluation result output section 20 Terminal Equipment 21 Control section 22 Input section 23 Display section

Claims

1. a document data acquisition unit for acquiring document data including at least a character string object; a pre-processing unit that performs pre-processing on the document data acquired by the document data acquisition unit; an information amount evaluation unit that evaluates an information amount of the document data based on the preprocessed document data; a character evaluation unit that evaluates the readability of the character string based on the preprocessed document data; a color evaluation unit that evaluates a relationship between adjacent colors in the document data based on the preprocessed document data.

2. 2. The document evaluation device according to claim 1, wherein the preprocessing unit performs a process of removing objects that are not to be evaluated from the document data as the preprocessing.

3. 2. The document evaluation device according to claim 1, further comprising an evaluation result output section for outputting evaluation results of said information amount evaluation section, said character evaluation section and said color evaluation section.

4. 2. The document evaluation device according to claim 1, wherein the document data includes vector graphic objects and bitmap image objects.

5. 2. The document evaluation device according to claim 1, wherein the document data includes font information of the character string.

6. 2. The document evaluation device according to claim 1, wherein the evaluation result output unit outputs, as the evaluation result, information indicating a position of a target to be warned in the document data.

7. 7. The document evaluation device according to claim 6, wherein, when the document data includes information on page rotation, the evaluation result output unit performs coordinate conversion processing corresponding to the page rotation on information indicating the position of the warning target in the document data.

8. A document evaluation device according to any one of claims 1 to 7, and a terminal device for displaying an evaluation result in the character evaluation device.

9. Obtain document data that contains at least a string object, performing preprocessing on the acquired document data; Evaluating an information content of the document data based on the preprocessed document data; evaluating the readability of the character string based on the preprocessed document data; A document evaluation method for evaluating a relationship between adjacent colors in the document data based on the preprocessed document data.

10. obtaining document data including at least a character string object; performing pre-processing on the acquired document data; evaluating an information content of the document data based on the preprocessed document data; evaluating the readability of the character string based on the preprocessed document data; and evaluating a relationship between adjacent colors in the document data based on the preprocessed document data.

Images