Information processing devices and non-volatile storage media

Abstract

This invention provides an information processing apparatus and a non-volatile storage medium capable of verifying the colorimetric recognizability of produced content, and capable of appropriate verification without being overly sensitive at high precision. The information processing apparatus (10) for evaluating the colorimetric recognizability of content includes: a transformation unit (S12) that transforms the color space values ​​of the first and second verification points (A, B) on the content into Lab color space values; a calculation unit (S13) that calculates the color difference and lightness difference between the first and second verification points based on the Lab color space values; and a recognizability determination unit (S23, S24) that compares a color difference threshold with the color difference between the first and second verification points to determine color difference recognizability, and compares a lightness difference threshold with the lightness difference between the first and second verification points to determine lightness difference recognizability. The color difference threshold and the lightness difference threshold are set to different values ​​depending on whether the area including the first verification point and the area including the second verification point are adjacent.

Description

Technical Field

[0001] The embodiments of the present invention relate to an information processing device for verifying the color recognition of documents, patterns, images and other content, as well as a non-volatile storage medium. Background Technology

[0002] Documents, patterns, images, and other content are generally represented using multiple colors. Using multiple colors can be expected to improve visual recognition or intuitive perception, and also increase the amount of information conveyed. It is important that this content is easily identifiable and presented without information degradation, not only for people with normal color vision, but also for people with color vision deficiencies and the elderly.

[0003] The aim is to verify whether the content being produced consists of color combinations that can be recognized by people with normal color vision, people with color vision disorders, the elderly, and all other categories of color vision characteristics; that is, to verify whether it has color vision recognition capability.

[0004] However, the current situation is that even if there are methods to assist in color specification when creating content, there is no method that can properly verify the color recognition of the created content without being overly sensitive even at high precision. Summary of the Invention

[0005] The problem the invention aims to solve

[0006] The goal is to verify the colorimetric recognizability of the produced content, and to properly verify colorimetric recognizability without being overly sensitive even at high precision.

[0007] means for solving problems

[0008] The information processing apparatus of this embodiment, used for evaluating the color recognition of content, includes:

[0009] The storage unit stores a program, a first and a second reference threshold for determining color difference recognition, a third and a fourth reference threshold for determining lightness difference recognition, and data associated with multiple Lab color space values ​​for correcting the first to the fourth reference thresholds.

[0010] The processor executes the above program;

[0011] In the information processing device, the processor executes the program to achieve the functions of the following parts:

[0012] The transformation unit converts the color space values ​​of the first and second verification points specified by the user on the content into Lab color space values.

[0013] The calculation unit, based on the Lab color space values, calculates the color difference and lightness difference between the first verification point and the second verification point.

[0014] The region determination unit, based on the color space values ​​of the content, determines whether the region including the first verification point and the region including the second verification point are adjacent or isolated.

[0015] The selection unit, based on the determination results of the adjacent and isolated conditions, selects one of the first and second reference thresholds, and one of the third and fourth reference thresholds.

[0016] The calibration unit, using the calibration coefficient associated with the Lab color space value of one of the first verification point and the second verification point, corrects one of the selected first reference threshold and the second reference threshold, as well as one of the third reference threshold and the fourth reference threshold, respectively.

[0017] The recognition determination unit compares one of the corrected first reference threshold and the second reference threshold with the color difference between the first verification point and the second verification point to determine the color difference recognition, and compares one of the corrected third reference threshold and the fourth reference threshold with the brightness difference between the first verification point and the second verification point to determine the brightness difference recognition. Attached Figure Description

[0018] Figure 1 This is a diagram showing the structure of the information processing apparatus according to this embodiment.

[0019] Figure 2 This is a flowchart illustrating the sequence of color vision recognition verification processes in this embodiment.

[0020] Figure 3 It shows through Figure 2 A diagram showing an example of the verification point specified in process S11.

[0021] Figure 4 It shows through Figure 2 The figure shows an example of the comprehensive judgment result obtained from process S25.

[0022] Explanation of reference numerals in the attached figures

[0023] 10: Information processing devices

[0024] 11: Processor

[0025] 13: RAM

[0026] 15: ROM

[0027] 17: Input controller

[0028] 19: Input devices

[0029] 21: Video controller

[0030] 23: Monitor,

[0031] 25: I / O controller,

[0032] 27: Storage Department. Detailed Implementation

[0033] Hereinafter, the information processing apparatus of this embodiment will be described with reference to the accompanying drawings.

[0034] Furthermore, in this embodiment, colors are represented using Lab color space values. As is known, the lightness or darkness of an appearance is represented by the lightness index L value, and hue and chroma are represented by the chromaticity indices a and b values. The lightness difference ΔL is provided as the difference in L values ​​between two colors. The color difference between two colors is a value that quantifies the perceived difference between two colors using L, a, and b values. Various indices are used; for example, as the simplest indice, ΔE76 is provided as the distance between two color points in the Lab color space. For example, the color difference ΔE00 between two colors is obtained by defining a calculation formula in a way that approximates the color recognition area of ​​the human eye in the Lab color space based on the calculated color difference. Since this calculation formula is known, its explanation is omitted here. In this embodiment, any index from various indices can be used as the color difference. Furthermore, as objects for verifying color perception recognition through this embodiment, examples include documents, charts, diagrams, images, etc. This content can be represented using any color space, such as RGB (Red, Green, Blue: the three primary colors) or CMYK (Cyan, Magenta, Yellow, Black: the four primary colors for printing). For ease of explanation, we will assume that the content is represented using RGB color space values.

[0035] Figure 1This is a block diagram illustrating the structure of the information processing apparatus 10 according to this embodiment. The information processing apparatus 10 includes a processor 11, RAM (Random Access Memory) 13, ROM (Read-Only Memory) 15, an input controller 17, an input device 19, a video controller 21, a display 23, an I / O controller 25, and a storage unit 27. The processor 11 is, for example, composed of a CPU (Central Processing Unit) and a GPU (Graphics Processing Unit). The RAM 13 functions as the main memory and working area of ​​the processor 11. The processor 11 executes various operations by loading programs required for processing from the ROM 15 or the storage unit 27 into the RAM 13. The ROM 15 or the storage unit 27 stores the BIOS (Basic Input Output System), operating system program (OS), code for a program that performs color vision recognition verification processing, and various data required by the program, which are executed by the processor 11. Details will be described later.

[0036] Input controller 17 controls input from input devices 19, such as keyboards (KB), mice, or touchscreens. Video controller 21, under the control of processor 11, controls the display on monitor 23, such as an LCD (Liquid Crystal Display). I / O controller 25 controls access to storage unit 27.

[0037] Tables 1, 2, 3, and 4 illustrate the examples. Figure 1 The storage unit stores Lab values ​​for individuals with normal color vision, those with color vision deficiency (Type P), those with color vision deficiency (Type D), and the elderly. Tables 1, 2, 3, and 4 show the Lab color space value tables stored in the storage unit 27. In each Lab color space value table, for each color number among multiple color numbers, there is a corresponding group of L*, a*, and b* values ​​(hereinafter simply labeled L, a, and b values) and a correction coefficient for the reference threshold used to correct color vision recognition. The Lab color space value tables are structured according to various color vision characteristics, such as those of individuals with normal color vision, those with color vision deficiency (Type P), those with color vision deficiency (Type D), and the elderly. As is known, the L value represents the lightness of the color. Furthermore, the a value represents the position between red / magenta and green, and the b value represents the position between yellow and blue; hue is defined by the a and b values.

[0038] The correction coefficients are predetermined based on color vision characteristic classification and hue. Details will be described later, but for example, to determine the recognizability of color differences, a threshold is compared between two verification points. When the color difference exceeds the threshold, it is determined that there is color difference recognizability between the two verification points or between two regions each including the two verification points; when the color difference is below the threshold, it is determined that there is no color difference recognizability. In cases where strict requirements are placed on the determination of color difference recognizability, a higher threshold is required. Here, the inventors discovered that color difference recognizability changes not only based on color vision characteristic classification but also based on hue. The same applies to lightness difference recognizability. Therefore, to improve the accuracy of determining color difference recognizability and lightness difference recognizability, the reference threshold is associated with the color vision characteristic classification one by one, and the correction coefficients used to correct the reference threshold are associated with the hue separately.

[0039] Table 1

[0040] Lab color space values ​​for people with normal color vision

[0041]

[0042] Table 2

[0043] People with color vision deficiency (Type P) use the Lab color space value table.

[0044]

[0045] Table 3

[0046] People with color vision deficiency (Type D) use the Lab color space value table.

[0047]

[0048] Table 4

[0049] Lab color space value table for the elderly

[0050]

[0051] Tables 5 and 6 show, respectively Figure 1The storage unit 27 stores a reference threshold table for adjacent areas and a reference threshold table for isolation. In the reference threshold tables, the reference thresholds for determining color difference recognition and the reference thresholds for determining lightness difference recognition are associated with each color vision characteristic category, such as people with normal color vision, people with color vision deficiency (Type P), people with color vision deficiency (Type D), and the elderly. Here, the inventors discovered that the perceived color difference recognition and lightness difference recognition change when areas are adjacent (near each other) and when areas are isolated (not adjacent, other areas exist between areas). In the adjacent area state, both color difference recognition and lightness difference recognition are lower than in the isolated area state. Therefore, two benchmark threshold tables, Table 5 and Table 6, are set up to be used separately according to the adjacent / isolated states between regions. Table 5 corresponds to the state where two regions with two verification points are adjacent, while Table 6 corresponds to the state where two regions are not adjacent, i.e., isolated by other regions. Specifically, by setting the thresholds related to color difference and lightness difference applicable when regions are adjacent to each other to higher values ​​than the thresholds applicable when regions are isolated, the accuracy of color difference recognition and lightness difference recognition is improved. In addition, the benchmark thresholds related to color difference shown in Table 5 are the first benchmark thresholds, the benchmark thresholds related to color difference shown in Table 6 are the second benchmark thresholds, the benchmark thresholds related to lightness difference shown in Table 5 are the third benchmark thresholds, and the benchmark thresholds related to lightness difference shown in Table 6 are the fourth benchmark thresholds.

[0052] Table 5

[0053] The baseline threshold used for adjacent (nearest) connections

[0054] Classification of color vision characteristics Color difference (ΔE76) Lightness difference (ΔL) People with normal color vision (c 30.0 15.0 People with color vision deficiency (Type P) 30.0 15.0 People with color vision deficiency (Type D) 30.0 15.0 elderly 30.0 20.0

[0055] Table 6

[0056] The baseline threshold for isolation (non-adjacent)

[0057] Classification of color vision characteristics Color difference (ΔE76) Lightness difference (ΔL) People with normal color vision (C 25.0 13.0 People with color vision deficiency (Type P) 25.0 14.0 People with color vision deficiency (Type D) 25.0 14.0 elderly 25.0 18.0

[0058] exist Figure 2 The diagram illustrates the color vision recognition verification process performed according to this embodiment. Each unit of the color vision recognition verification process is implemented by loading the code of the program used to perform the color vision recognition verification process from the storage unit 27 into the RAM 13, and then executing the program by the processor 11.

[0059] In process S11, through the operator's operation of input device 19, multiple verification points are assigned to arbitrary positions on the content. Here, as... Figure 3As illustrated, three verification points A, B, and C are specified. The following process is used to determine the presence or absence of color recognition between each pair of verification points in all combinations (A / B, A / C, B / C).

[0060] Tables 7 and 8 respectively show the results related to... Figure 2 Examples of color difference and lightness difference between verification points A, B, and C, determined in step S12, and each color vision characteristic category related to them, and calculated in step S13, related to each color vision characteristic category (A / B, A / C, B / C). In step S12, as illustrated in Table 7, the RGB color space values ​​of each verification point A, B, and C are transformed to Lab color space values, for example. This transformation process is performed for each color vision characteristic category, such as people with normal color vision, people with color vision deficiency (Type P), people with color vision deficiency (Type D), and the elderly. In step S13, as illustrated in Table 8, based on the Lab color space values ​​of each verification point A, B, and C, the color difference and lightness difference between the two verification points (A / B, A / C, B / C) are calculated for each color vision characteristic category. The color difference between two points is obtained by quantifying the perceived difference between two colors using the L, a, and b values ​​of each point. Various indices are used; for example, as the simplest indice, ΔE76 is provided as the distance between two color points in the Lab color space. There are various methods for calculating this color difference, but since these methods are well-known, their explanation is omitted here. Additionally, the lightness difference is calculated as the difference in L values ​​between two points.

[0061] Table 7

[0062]

[0063] Table 8

[0064]

[0065] Tables 9 and 10 respectively show the results related to... Figure 2 The correction coefficients for each color vision characteristic classification related to each verification point A, B, C read in step S14, the reference threshold read in step S20, the threshold corrected in step S21, and examples of the thresholds selected between each verification point (A / B, A / C, B / C).

[0066] In process S14, as illustrated in Table 9, the Lab color space value table is consulted based on the Lab color space values ​​of each verification point A, B, and C, and the correction coefficients corresponding to each verification point A, B, and C are read from the storage unit 27 into the RAM 13 for each color vision characteristic category.

[0067] Table 9

[0068]

[0069] In step S15, regions RA, RB, and RC, including each verification point A, B, and C, are extracted. Any method can be used for region extraction. For example, the RGB color space values ​​of each verification point A, B, and C, or values ​​approximate to those values, can be used as thresholds for binarization, and the enclosed space including verification points A, B, and C can be extracted as regions RA, RB, and RC, including each verification point A, B, and C.

[0070] In step S16, it is determined whether the regions RA, RB, and RC of each verification point A, B, and C are in an adjacent state (neighboring), or an isolated state (not adjacent, with other regions existing between them). For example, regions RA, RB, and RC are dilated, and a predetermined threshold is compared with the number of pixels in the overlapping portion. If the number of pixels in the overlapping portion exceeds the threshold, they are determined to be in an adjacent state; if the number of pixels in the overlapping portion is below the threshold, they are determined to be in an isolated state.

[0071] Then, in step S17, a combination of two verification points from verification points A, B, and C is selected. For example, verification points A and B are selected. In step S18, based on the determination result of step S16, it is determined whether the regions RA and RB of the two selected verification points A and B are adjacent or isolated. If they are adjacent (yes), for each of the two verification points A and B and for each color vision characteristic, the reference thresholds for adjacent use (color difference) and the reference thresholds for adjacent use (lightness difference) shown in Table 5 are read (step S19). If they are isolated (no), for each of the two verification points A and B and for each color vision characteristic, the reference thresholds for isolation (color difference) and the reference thresholds for isolation (lightness difference) shown in Table 6 are read (step S20).

[0072] The reference thresholds for adjacent areas and for isolation areas differ. Typically, the reference threshold for adjacent areas is set higher than that for isolation areas, while the reference threshold for isolation areas is set lower than that for adjacent areas. In adjacent areas, the discernibility of color difference or lightness difference is judged more strictly. In non-adjacent areas, because other areas exist between them, a slightly more lenient judgment can be made compared to the adjacent case. This ensures a high level of accuracy in discernibility judgment while rejecting overly sensitive judgments.

[0073] In step S21, for each verification point A and B, the correction coefficients read in step S14 are used to classify and correct the reference threshold (color difference) and reference threshold (lightness difference) for each color vision characteristic. In step S22, as illustrated in Table 10, the reference threshold (referred to as the threshold) of the corrected color difference associated with verification point A is compared with the threshold of the color difference associated with verification point B, and a higher threshold is selected for each color vision characteristic classification. Regarding lightness difference, a comparison is also made between verification points A and B, and a higher threshold is selected for each color vision characteristic classification. Furthermore, selecting a higher threshold implies a more rigorous and precise determination of the recognizability of color difference or lightness difference, but does not preclude the selection of a lower threshold between verification points A and B.

[0074] Table 10

[0075]

[0076] Table 11 shows the results of... Figure 2 Examples of judgment results obtained from processes S23 and S24, and comprehensive judgment results obtained from process S25.

[0077] Table 11

[0078]

[0079] In step S23, as illustrated in Table 11, for the selected threshold (color difference), the color difference between verification points A and B calculated in step S13 is compared. If the color difference between verification points A and B exceeds the threshold (color difference), it is determined that there is color difference discernibility between verification points A and B (marked with ○). On the other hand, if the color difference between verification points A and B is below the threshold (color difference), it is determined that there is no color difference discernibility between verification points A and B (marked with ×). This color difference discernibility determination is performed for each color vision characteristic category.

[0080] Similarly, in step S24, for the selected threshold (lightness difference), the lightness difference between verification points A and B calculated in step S13 is compared. If the lightness difference between verification points A and B exceeds the threshold (lightness difference), it is determined that there is lightness difference identifiability between verification points A and B. On the other hand, if the lightness difference between verification points A and B is below the threshold (lightness difference), it is determined that there is no lightness difference identifiability between verification points A and B. This determination of lightness difference identifiability is performed for each color vision characteristic category.

[0081] In step S25, as illustrated in Table 11, the overall recognizability between verification points A and B is determined based on color difference recognizability and lightness difference recognizability. If both color difference recognizability and lightness difference recognizability are recognizable for all color vision characteristic categories, it is determined that there is overall color vision recognizability between verification points A and B. If, for all color vision characteristic categories, one or both of color difference recognizability and lightness difference recognizability are not recognizable, it is determined that there is no overall color vision recognizability between verification points A and B.

[0082] If there are other groups of verification points in step S26, return to step S17 and execute steps S17 to S25 for the other groups of verification points to determine the overall color perception recognition among the other groups of verification points. In this case, determine whether there is overall color perception recognition between verification points A and C, and whether there is overall color perception recognition between verification points B and C.

[0083] If step S26 is "No," meaning that a comprehensive color perception assessment has been completed for all combinations of verification points, then in step S27, the comprehensive color perception assessment results related to all combinations of verification points are presented in a table format, such as... Figure 4 As shown, it is represented by overlapping content.

[0084] According to the above-described embodiment, the color recognition of the produced content can be comprehensively verified from two aspects: color difference and lightness difference, and further across multiple color vision characteristic classifications, including people with normal color vision, people with color vision deficiency (Type P), people with color vision deficiency (Type D), and the elderly. Furthermore, by using different thresholds to determine the presence or absence of color recognition between verification points in states where the verification points are adjacent and states where the regions are isolated, the verification accuracy can be improved. Moreover, by using correction coefficients corresponding to hue (a value, b value) to correct the reference threshold, the verification accuracy can be further improved.

[0085] While some embodiments of the invention have been described, these embodiments are presented by way of example and are not intended to limit the scope of the invention. These embodiments can be implemented in various other ways, and various omissions, substitutions, and modifications can be made without departing from the spirit of the invention. These embodiments or variations thereof are included within the scope of the invention as contained in the scope or spirit of the invention, and within the scope of the claims and their equivalents.

Claims

1. An information processing device for evaluating the colorimetric recognizability of content, comprising: The storage unit stores a program, a first and a second reference threshold for determining color difference recognition, a third and a fourth reference threshold for determining lightness difference recognition, and data associated with multiple Lab color space values ​​for correcting the first to the fourth reference thresholds. The processor executes the program; The information processing device is characterized in that... The processor executes the program to achieve the following functions: The transformation unit converts the color space values ​​of the first and second verification points specified by the user on the content into Lab color space values. The calculation unit, based on the Lab color space values, calculates the color difference and lightness difference between the first verification point and the second verification point. The region determination unit, based on the color space values ​​of the content, determines whether the region including the first verification point and the region including the second verification point are adjacent or isolated. The selection unit, based on the determination results of the adjacent and isolated conditions, selects one of the first and second reference thresholds, and also selects one of the third and fourth reference thresholds. The calibration unit, using the calibration coefficient associated with the Lab color space value of one of the first verification point and the second verification point, corrects one of the selected first reference threshold and the second reference threshold, as well as one of the third reference threshold and the fourth reference threshold, respectively. The recognition determination unit compares one of the corrected first reference threshold and the second reference threshold with the color difference between the first verification point and the second verification point to determine the color difference recognition, and compares one of the corrected third reference threshold and the fourth reference threshold with the brightness difference between the first verification point and the second verification point to determine the brightness difference recognition.

2. The information processing device according to claim 1, characterized in that, To further realize the functions of the comprehensive judgment department, The comprehensive judgment unit determines the comprehensive color perception recognition between the first verification point and the second verification point based on the judgment results of the color difference recognition and the lightness difference recognition.

3. The information processing device according to claim 1, characterized in that, The first to the fourth benchmark thresholds are set for people with normal color vision, people with color vision deficiency, and the elderly, respectively.

4. The information processing apparatus according to claim 2, characterized in that, The aforementioned correction coefficients are set separately for people with normal color vision, people with color vision deficiency, and the elderly.

5. The information processing apparatus according to claim 4, characterized in that, The transformation unit transforms the color space values ​​into Lab color space values ​​for the person with normal color vision, the person with color vision deficiency, and the elderly, respectively. The calculation unit calculates the color difference and brightness difference between the first verification point and the second verification point based on the Lab color space values ​​for the person with normal color vision, the person with color vision deficiency, and the elderly. The correction unit uses the correction coefficient to correct one of the first and second reference thresholds and one of the third and fourth reference thresholds for the person with normal color vision, the person with color vision deficiency, and the elderly, respectively. The recognition determination unit determines the color difference recognition for the person with normal color vision, the person with color vision deficiency, and the elderly person, respectively, and determines the lightness difference recognition for the same three groups. If the comprehensive judgment unit determines that the person with normal color vision, the person with color vision impairment, and the elderly all have the color difference recognition ability and the lightness difference recognition ability, it has comprehensive color vision recognition ability between the first verification point and the second verification point.

6. An information processing apparatus for evaluating the colorimetric recognizability of content, the information processing apparatus being characterized by having: The transformation unit transforms the color space values ​​of the first and second verification points in the content into Lab color space values. The calculation unit calculates the color difference and lightness difference between the first verification point and the second verification point based on the Lab color space values. The recognition ability determination unit compares the color difference threshold with the color difference between the first verification point and the second verification point to determine the color difference recognition ability, and compares the brightness difference threshold with the brightness difference between the first verification point and the second verification point to determine the brightness difference recognition ability. The color difference threshold and the brightness difference threshold are set to different values ​​based on whether the region including the first verification point and the region including the second verification point are adjacent.

7. A non-volatile storage medium readable by a computer, characterized in that it stores a program for enabling the computer to perform the functions of the following units: The transformation unit converts the color space values ​​of the first and second verification points, specified by the user, into Lab color space values. The calculation unit, based on the Lab color space values, calculates the color difference and lightness difference between the first verification point and the second verification point. The region determination unit, based on the color space values ​​of the content, determines whether the region including the first verification point and the region including the second verification point are adjacent or isolated. The selection unit, based on the determination results of the adjacent and isolated conditions, selects one of a first reference threshold and a second reference threshold for determining color difference recognition, and selects one of a third reference threshold and a fourth reference threshold for determining brightness difference recognition. The correction unit, using correction coefficients associated with the Lab color space value of either the first verification point or the second verification point, corrects one of the selected first reference threshold and the second reference threshold, as well as one of the third reference threshold and the fourth reference threshold, respectively. The recognition determination unit compares one of the corrected first reference threshold and the second reference threshold with the color difference between the first verification point and the second verification point to determine the color difference recognition, and compares one of the corrected third reference threshold and the fourth reference threshold with the brightness difference between the first verification point and the second verification point to determine the brightness difference recognition.

8. A non-volatile storage medium readable by a computer, characterized in that it stores a program for enabling the computer to perform the functions of the following units: The transformation unit converts the color space values ​​of the first and second verification points in the content to Lab color space values. The calculation unit, based on the Lab color space values, calculates the color difference and lightness difference between the first verification point and the second verification point. The recognition ability determination unit compares the color difference threshold with the color difference between the first verification point and the second verification point to determine the color difference recognition ability, and compares the brightness difference threshold with the brightness difference between the first verification point and the second verification point to determine the brightness difference recognition ability. The setting unit sets the color difference threshold and the brightness difference threshold to different values ​​depending on whether the area including the first verification point and the area including the second verification point are adjacent or isolated.

Images