Judgment system, color judgment method, program, information processing system, terminal device, and label marker

Abstract

The present application provides a judgment system, a color judgment method, a program, an information processing system, a terminal device, and a label marker, which can judge the color of an environmental detection region having a color that changes due to environmental changes in a data region and an encoding label to which a two-dimensional code or a bar code currently in circulation is applied with high precision and easily without setting a reference region for correcting a hue deviation caused by a setting environment. A judgment system that judges the color of a judgment object includes a storage device that stores a judgment line that uses the lightness and saturation of the color of the judgment object as parameters, and a data processing device that acquires color information of the color of the judgment object, judges the color of the judgment object based on the color information, and includes a color judgment section that calculates a feature amount with respect to the lightness of the color information, that is, the vector length of the color information, and a feature amount with respect to the saturation, that is, the vector direction of the color information, in a color space, compares the judgment line, and thereby judges the color of the judgment object.

Description

Technical Field

[0001] This invention relates to a color determination system, color determination method, program, information processing system, terminal device, and label for determining the color of a specified area. Background Technology

[0002] It is known to have an indicator sign for predicting the environment in which a QR code is exposed, and a management system for applying such an indicator sign. Patent Document 1 (Japanese Patent Application Publication No. 2024-10275) describes a QR code identification system comprising: an image acquisition device for acquiring a QR code image, having a positioning pattern with a reference color used to determine the amount of color change corresponding to the shooting environment; a data processing device; and a storage device for storing color information of the reference color and position information of the reference color and ink. The data processing device detects the coordinates of the four corners of the QR code image and determines the position of the area for detecting color information, detects the color information of the area, the area including a reference color area and an ink area, determines the reference color area and the ink area based on the position information of the reference color stored in the storage device and the color information and position of the area, and corrects the color information of the ink area using the relationship between the color information of the reference color stored in the storage device and the detected color information of the reference color area.

[0003] Existing technical documents

[0004] Patent documents

[0005] Patent Document 1: Japanese Patent Application Publication No. 2024-10275 Summary of the Invention

[0006] The technical problem that the invention aims to solve

[0007] The invention described in Patent Document 1 improves the accuracy and reading speed of color information acquisition in environmental detection areas where color changes due to environmental variations. However, to accurately determine the color of the temperature-indicating material, a reference color is needed to correct for differences in the color information read due to variations in shooting conditions. Therefore, for products that already have a QR code printed in black monochrome, a dedicated QR code with a reference color area set outside the temperature-indicating material is also required. The coexistence of different QR codes leads to problems such as increased complexity in application and difficulty in applying them to black monochrome printed barcodes.

[0008] In order to solve the above problems, the present invention aims to provide a judgment system that can determine the color reading information of environmental detection areas in the data area that have environmental detection areas whose colors change due to environmental changes and which use existing circulating QR codes or barcodes or coded labels, without setting up reference color areas for correction based on shooting conditions.

[0009] Technical means to solve the problem

[0010] The present invention, which achieves the above objective, is a judgment system for judging the color of a judgment object, comprising: a storage device storing a judgment line with the lightness and saturation of the color of the judgment object as parameters; and a data processing device acquiring color information of the color of the judgment object and judging the color of the judgment object based on the color information; the data processing device comprising: a color judgment unit calculating a feature quantity of the lightness of the color information (i.e., the vector length of the color information) and a feature quantity of the saturation of the color information (i.e., the vector direction of the color information) in the color space, comparing them with the judgment line, thereby judging the color of the judgment object.

[0011] Other aspects of the invention will be described in the embodiments described below.

[0012] Invention Effects

[0013] According to the present invention, a judgment system can be provided that can determine the color of an environmental detection area in a data area that has an environmental detection area whose color changes with environmental changes and which uses an existing QR code or barcode encoding label without setting up a reference area for correcting color information differences caused by differences in shooting conditions.

[0014] Other technical issues, technical features, and technical effects not mentioned above will become clear through the following description of the implementation methods. Attached Figure Description

[0015] Figure 1A This is a schematic diagram of the label in Example 1.

[0016] Figure 1B This is a schematic diagram of the finder pattern in Example 1.

[0017] Figure 1C This is a schematic diagram of the alignment pattern in Example 1.

[0018] Figure 2A This is a schematic diagram of the label in Example 1 before and after environmental changes.

[0019] Figure 2B This is an example of setting up an environmental change area in Example 1.

[0020] Figure 2C This is an example of setting up an environmental change area in Example 1.

[0021] Figure 2D This is an example of setting up an environmental change area in Example 1.

[0022] Figure 2E This is an example of setting up an environmental change area in Example 1.

[0023] Figure 2F This is an example of setting up an environmental change area in Example 1.

[0024] Figure 2G This is an example of setting up an environmental change area in Example 1.

[0025] Figure 2H This is an example of setting up an environmental change area in Example 1.

[0026] Figure 2I This is an example of setting up an environmental change area in Example 1.

[0027] Figure 2J This is an example of setting up an environmental change area in Example 1.

[0028] Figure 2K This is an example of setting up an environmental change area in Example 1.

[0029] Figure 2L This is an example of setting up an environmental change area in Example 1.

[0030] Figure 2M This is an example of setting up an environmental change area in Example 1.

[0031] Figure 2N This is an example of setting up an environmental change area in Example 1.

[0032] Figure 2O This is an example of setting up an environmental change area in Example 1.

[0033] Figure 3A This is an example of setting up an environmental change area in Example 1.

[0034] Figure 3B This is an example of setting up an environmental change area in Example 1.

[0035] Figure 3C This is an example of setting up an environmental change area in Example 1.

[0036] Figure 3D This is an example of setting up an environmental change area in Example 1.

[0037] Figure 3E This is an example of setting up an environmental change area in Example 1.

[0038] Figure 3F This is an example of setting up an environmental change area in Example 1.

[0039] Figure 4This is a diagram illustrating the RGB space of the colors in the environmental change area of ​​Example 1.

[0040] Figure 5 This is a flowchart illustrating the color determination process of Example 1.

[0041] Figure 6A This is a diagram illustrating the method for determining the color of the environmental change area in Example 1.

[0042] Figure 6B This is a diagram illustrating the method for determining the color of the environmental change area in Example 1.

[0043] Figure 6C This is a diagram illustrating the method for determining the color of the environmental change area in Example 1.

[0044] Figure 7 This is a diagram illustrating the method for determining the color of the environmental change area in Example 1.

[0045] Figure 8A This is a diagram illustrating the method for determining the color of the environmental change area in Example 1.

[0046] Figure 8B This is a diagram illustrating the method for determining the color of the environmental change area in Example 1.

[0047] Figure 8C This is a diagram illustrating the method for determining the color of the environmental change area in Example 1.

[0048] Figure 9A This is a diagram illustrating the method for determining the color of the environmental change area in Example 1.

[0049] Figure 9B This is a diagram illustrating the method for determining the color of the environmental change area in Example 1.

[0050] Figure 9C This is a diagram illustrating the method for determining the color of the environmental change area in Example 1.

[0051] Figure 10 This is a structural diagram of the judgment system in Example 1.

[0052] Figure 11 This is a flowchart of the judgment system in Example 1.

[0053] Figure 12 This is an example of displaying the output result of the judgment system in Example 1.

[0054] Figure 13 This is an example of displaying the input information of the judgment system in Embodiment 1.

[0055] Figure 14This is a diagram illustrating the outline of the information processing system using the judgment system of Embodiment 2.

[0056] Figure 15A This is a graph showing the experimental results of the judgment system in Example 3.

[0057] Figure 15B This is a graph showing the experimental results of the judgment system in Example 3.

[0058] Figure 15C This is a graph showing the experimental results of the judgment system in Example 3.

[0059] Figure 15D This is a graph showing the experimental results of the judgment system in Example 3.

[0060] Figure 16 This is a graph showing the experimental results of the judgment system in Example 4.

[0061] Figure 17A This is a diagram illustrating an example of the labeling material of Example 1.

[0062] Figure 17B This is a diagram illustrating an example of the labeling material of Example 1.

[0063] Figure 17C This is a diagram illustrating an example of the labeling material of Example 1. Detailed Implementation

[0064] The following describes embodiments of the present invention, but the present invention is not limited to the following description and can be implemented in any modified form without significantly impairing the effects of the present invention. The present invention can be implemented by combining different embodiments with each other. In the following description, the same reference numerals are used to refer to the same parts in different embodiments, and repeated descriptions are omitted.

[0065] Furthermore, in the following descriptions, when explaining the processing performed by the program, the descriptions may sometimes focus on the program or functional units, but the hardware component of these is a processor or an information processing device (computer) comprising such a processor. The information processing device uses the processor to appropriately utilize resources such as memory and communication interfaces to execute processing according to the program read into memory. The processor is not limited to a CPU; a GPU (Graphical Processing Unit) or similar device can also be used. Furthermore, the processing to implement the function is not limited to software program processing; it can also be implemented using dedicated circuits. Dedicated circuits can use FPGAs (Field Programmable Gate Arrays), ASICs (Application Specific Integrated Circuits), etc.

[0066] Example 1

[0067] <QR code>

[0068] First, the label with a QR code configured in Embodiment 1 of the present invention will be described. Various QR codes can be used in this judgment system; the following description uses a QR code (registered trademark) as an example. The QR code standard is defined by ISO / IEC 18004, etc. Furthermore, under the condition of a fixed area, QR codes such as PDF417, DataMatrix, Maxicode, and AztecCode can also be used.

[0069] Figure 1A This is a schematic diagram of a label 100 configured with a QR code 200 according to this embodiment. The label 100 consists of a QR code 200 and an environmental detection area 600. The QR code 200 has three finder patterns 300a, 300b, and 300c (positioning patterns) arranged at the three corners of the QR code 200 for position detection, cells 500 constituting the data area, and a correction pattern 400 for correcting the positional offset of the cells 500 caused by deformation.

[0070] The QR code 200 further has an environmental detection area 600 configured to overlap with the data area composed of units 500. The environmental detection area 600 is an area whose color changes due to environmental changes (e.g., from black to red).

[0071] In addition to QR codes, this technology can also be applied to QR codes with fixed internal patterns of fixed position and color. For example, when using PDF417, the start and end patterns can be configured as reference areas; when using DataMatrix, the calibration and clock patterns can be configured as reference areas; and when using MaxiCode or AztecCode, the central lookahead pattern can be configured as a reference area.

[0072] The label 100 can be affixed to other items in the form of a sticker. Sticker-type labels are preferred in terms of ease of use, setup, and cost, but any form such as a tag or card can also be used to correspond to the managed goods.

[0073] in addition, Figure 1A The QR code 200 is, for example, version 2 (25×25 units). The unit structure (version) of the QR code can be changed according to the content of the information to be input, but version 2 or above is preferred in terms of configuring the correction pattern 400 for correcting deformation.

[0074] in addition, Figure 1A For example, the QR code 200 is a QR code with an error correction level of "H". The error correction level of a QR code can be reduced in accordance with the amount of information and its purpose, but by configuring an environmental detection area 600 within the QR code, in order to prevent the QR code from being deliberately damaged or to prevent reading problems caused by stains, dirt, or damage during logistics, the preferred error correction level is "H".

[0075] The environmental detection area 600 configured within the QR code 200 can be any medium, such as ink, whose color changes with environmental changes; there are no particular restrictions. However, in terms of manufacturing process, an ink form that can be printed on the QR code 200 is preferred. Examples of the environmental detection area 600 include using color changes to reflect environmental conditions such as temperature, temperature history, humidity, light, gas concentration, and vibration; detecting the pH of liquids; the concentration of various ions in liquids; the concentration of various reagents; the concentration of various amino acids / proteins; and the presence of viruses / bacteria. Furthermore, the information detected by this environmental detection area 600 can also be used to calculate environmental changes.

[0076] In this embodiment, the RGB (Red, Green, Blue) model is used as the color model for illustration. In the RGB model, the colors constituting an image are expressed by combinations of values ​​for each of the three colors: R (red), G (green), and B (blue), ranging from the darkest value of 0 to the brightest value of 255. Hereinafter, RGB components are represented in square brackets in the form of [R,G,B], for example, red [255,0,0], the darkest black [0,0,0], and the brightest white [255,255,255]. Furthermore, in the QR code 200 of this embodiment, the colors of the tinted portions (e.g., unit 500) that are not specifically mentioned are black or colors equivalent to black.

[0077] Figure 1B This is an enlarged view of the lookahead patterns 300a-300c within the QR code 200. The lookahead patterns 300a-300c consist of a first lookahead pattern area 310, a second lookahead pattern 320, and a third lookahead pattern 330. These lookahead patterns can be used to identify the location of the QR code, enabling high-speed reading.

[0078] In addition, the lookup pattern needs to maintain the function of recognizing the QR code position. Therefore, the lookup patterns 300a to 300c need to be configured with a ratio of 1:1:3:1:1 for white (light) units and black (dark) units at any position in the A, B, and C directions. As long as the above ratio is maintained, any color scheme can be used.

[0079] In addition, the first lookup pattern area 310, the second lookup pattern area 320, and the third lookup pattern 330 can be any color that the QR code reader can read, without any particular limitation. However, the colors used in the first lookup pattern area 310 and the third lookup pattern area 330 are preferably identified as the same as dark, low-brightness colors (e.g., black), and the colors used in the second lookup pattern area 320 are preferably identified as the same as light, high-brightness colors (e.g., white).

[0080] Figure 1C This is an enlarged view of the correction pattern 400 within the QR code 200. The correction pattern has the function of correcting the positional offset of each unit caused by deformation. The correction pattern consists of a first correction pattern area 410, a second correction pattern area 420, and a third correction pattern area 430.

[0081] The color of each correction pattern area can be any color that can be read by the QR code reader, without any particular limitation. However, the colors used in the first correction pattern area 410 and the third correction pattern area 430 are preferably identified as the same as dark, low-brightness colors (e.g., black), and the colors used in the second correction pattern area 420 are preferably identified as the same as light, high-brightness colors (e.g., white).

[0082] Next, in Figures 2A to 2F The diagram shows a structural example of an environmental detection area 600 when a QR code is used as a two-dimensional code 200.

[0083] Figure 2A Is with Figure 1A Similarly, an example is shown where an environmental detection area 600 is set in the center of the QR code 200, which is the basic form of a label, and an example of a first label 101 before an environmental change and a second label 102 after an environmental change. The color of the environmental detection area 600 changes from, for example, from black to red due to environmental changes.

[0084] Figure 2B The third label 103 shown is an example in which an environmental detection area 600 is set at any position inside the QR code 200 that does not overlap with the lookup pattern 300 and the correction pattern 400.

[0085] Figure 2C The fourth label 104 shown is an example of an environmental detection area 600 set at any position outside the QR code 200.

[0086] Figure 2D The fifth label 105 shown is a label placed at any position inside the QR code 200 that corresponds to... Figure 2A Examples of environmental detection areas of different shapes (600).

[0087] Figure 2E The sixth label 106 shown is an example of an environmental detection area 600 with a hollow shape set at any position inside the QR code 200.

[0088] Figure 2F The seventh label 107 shown is an example of an environmental detection area 600 with an elongated shape extending from the inside to the outside of the QR code 200.

[0089] Next, in Figures 2G to 2K The diagram shows a structural example of an environmental detection area 600 when the “Data Matrix” standard is used as a QR code 200 (201).

[0090] Figure 2G The eighth label 108 shown is an example where an environmental detection area 600 is set in the center inside the QR code 201.

[0091] Figure 2H The ninth label 109 shown is an example of an environmental detection area 600 with an elongated shape extending from the inside to the outside of the QR code 201.

[0092] Figure 2I The tenth label 110 shown is an example of an environmental detection area 600 set at any position outside the QR code 201.

[0093] Figure 2J The eleventh label 111 shown is an example of an environmental detection area 600 with a vertical rod shape set outside the QR code 201.

[0094] Figure 2K The twelfth label 112 shown is an example of an environmental detection area 600 with a rectangular shape surrounding the QR code 201.

[0095] in addition, Figures 2G to 2K The configuration structure can be applied not only to the "Data Matrix" standard, but also to other QR codes (Micro QR code, rMQR code, Aztec code, PDF417, MaxiCode, etc.).

[0096] Next, in Figures 2L to 2O The diagram shows a structural example of an environmental detection area 600 that uses the "GS1-128" standard as a barcode (202) instead of a QR code 200.

[0097] Figure 2L The thirteenth label 113 shown is an example where an environmental detection area 600 is set to the left of the barcode 202.

[0098] Figure 2M The fourteenth label 114 shown is an example where an environmental detection area 600 is set to the right of the barcode 202.

[0099] Figure 2N The fifteenth label 115 shown is an example of an environmental detection area 600 set on the upper side of the barcode 202.

[0100] Figure 2O The sixteenth label 116 shown is an example of an environmental detection area 600 set in the center inside the barcode 202.

[0101] in addition, Figures 2L to 2O The configuration structure can be applied not only to "GS1-128", but also to other one-dimensional codes (GS1 DataBar standards, EAN / UPC standards, ISBN / ISMN / ISSN code standards, etc.).

[0102] Able to be like the above Figures 2A to 2O The structure shown allows for arbitrary configuration of the shape and position of the environmental detection area 600, provided that it can read QR codes or 1D barcodes.

[0103] Next, other implementation methods for labels with environmental monitoring areas will be described. The above examples of labels envision the creation of new QR code labels that include environmental monitoring areas, but it is also possible to attach additional components with environmental monitoring areas to existing or separately created QR code labels that do not have environmental monitoring areas, thereby forming labels with environmental monitoring areas.

[0104] The following uses Figures 3A to 3F This section explains the specific setup method for the environmental monitoring area 600.

[0105] Figure 3A The circular environmental monitoring sticker 110 shown consists of an environmental monitoring area 600 and a circular transparent film 610.

[0106] Figure 3B yes Figure 3A The cross-sectional view shows that the circular environmental monitoring sticker 110 is set up in the form of a circular transparent film 610 covering the environmental monitoring area 600. Figure 3B In the illustration, the environmental detection area 600 and the circular transparent film 610 are shown separately for structural purposes, but they are actually arranged in contact.

[0107] Circular transparent film 610 is a transparent film that is transparent and difficult for moisture to pass through. There are no special restrictions. Representative general-purpose transparent films include PP (polypropylene), PET (polyethylene terephthalate), and PVC (polyvinyl chloride).

[0108] Figure 3C The method for setting a circular environmental detection sticker 110 on an existing QR code 200 involves affixing the circular environmental detection sticker 110 to the surface of the QR code 200. In this case, a portion of the existing QR code 200's pattern will be obscured by the circular environmental detection sticker 110. However, due to the QR code 200's own error correction function, as long as the obscured area is below the upper limit that the error correction level can reproduce, it can be read without problems.

[0109] Alternatively, the adhesive surface can be either the surface of the QR code 200 or the back of the circular environmental detection sticker 110. However, if the QR code 200 has already been placed on other products, it is preferable that the back of the circular environmental detection sticker 110 has an adhesive layer.

[0110] Figure 3D The environmental detection sticker 120 shown consists of an environmental detection area 600 and a square transparent film 620 with positioning guides 630.

[0111] Figure 3E yes Figure 3D The cross-sectional view shows that the guided environmental detection sticker 120 is set up in such a way that a square transparent film 620 covers the environmental detection area 600. Figure 3E In the diagram, the environmental detection area 600 and the square transparent film 620 are shown separately for structural purposes, but they are actually positioned in contact. The square transparent film 620 can use the same material as the circular transparent film 610.

[0112] Figure 3F This describes a method for setting a guided environmental detection sticker 120 on an existing QR code 200, wherein the guided environmental detection sticker 120 is affixed to the surface of the QR code 200. The affixing surface can be either the surface of the QR code 200 or the back of the guided environmental detection sticker 120; however, if the QR code 200 has already been affixed to other goods, it is preferable to have an adhesive layer on the back of the guided environmental detection sticker 120.

[0113] In addition, the above Figures 3A to 3F The structure is illustrated using a QR code as an example, but it can also be applied to one-dimensional codes such as barcodes.

[0114] Thus, as long as it is within the readable encoding range, the location of the environmental detection area (temperature detection ink) is not limited to the inside or outside of the encoding, and the shape of the environmental detection area (temperature detection ink) is also not limited.

[0115] <Method for Determining the Color of Environmental Monitoring Areas>

[0116] First, the color determination method for the environmental detection area in this embodiment will be explained.

[0117] In this embodiment, for the color of the environmental detection area 600, which includes hue changes (influences) caused by the setting environment (external light, etc.), the following is obtained: Figure 4 The RGB values ​​in the RGB (Red / Green / Blue) space shown are used as color information. Using the method described later, the normal color of the environment detection area 600 is determined without the need for color correction using reference areas, etc., thus eliminating the influence of the setting environment, etc. In this color determination, it is determined which of the two colors of the environment detection area 600 before and after the change is, for example, whether it is black before the change or red after the change (as described later, it is not limited to black / red determination, but can also determine the other two colors).

[0118] Figure 5 The color judgment process is as follows: First, in step S501, the RGB values ​​of the environment detection area 600 of the coded tag are obtained. Next, in step S502, based on the obtained RGB values, the feature quantities in the color space related to its vector length (VL) and its vector direction (SaturationLength SL) are calculated (the calculation methods of VL and SL are described later).

[0119] Then, in step S503, as follows Figure 6A The judgment line 603 shown is used as a threshold to determine whether it is color 1 or color 2 (the definition and generation method of judgment line 603 will be described later).

[0120] That is, such as Figure 6B As shown, the color is determined based on the positional relationship between the calculated VL and SL drawing point 610 and the judgment line 603. For example, if it is located in a larger area 601 relative to the judgment line 603, it is determined not to be "color 2". Figure 6C As shown, if the drawn point 620 is located in a smaller region 602 than the judgment line 603, it is judged as "color 2". Alternatively, if the color in the larger region 601 is predefined as "color 1", then... Figure 6B The color of the larger region 601 is determined to be "color 1".

[0121] This section explains the calculation methods for VL (vector length) and SL (saturation length), as well as the definition and generation method of the judgment line.

[0122] (1) Calculation methods of VL (vector length) and SL (saturation length)

[0123] (1-1) Convert the (R,G,B) values ​​to three-dimensional polar coordinates (r,θ,φ).

[0124] (R,G,B) and the three-dimensional polar coordinates (r,θ,φ) satisfy the following relationship:

[0125] [Formula 1]

[0126]

[0127] Here, r (Equation 1-4) is a parameter about the length (VL) of the RGB vector, and (θ,φ) is a parameter about the direction of the RGB vector.

[0128] (1-2) Extract the feature quantities of RGB vector length / RGB vector direction

[0129] r is used as the feature quantity of the RGB vector length. SL (saturation length) is defined as the feature quantity of the RGB vector direction according to θ and φ using the following formula.

[0130] [Equation 2]

[0131]

[0132] Where (θr, φr) is the reference point (constant) for saturation of 0, because it holds true when saturation is 0 (R=G=B), so θr and φr have the following values:

[0133] [Formula 3]

[0134]

[0135] Figure 7 This is a schematic diagram representing the SL (saturation length) calculated as described above.

[0136] Alternatively, lightness can be used instead of value (VL), and saturation can be used instead of saturation (SL). Lightness and saturation are generally calculated using the following formula:

[0137] [Formula 4]

[0138]

[0139] Figure 8A Is for Figures 6A-6C The example shown uses SL as the vertical axis and VL as the horizontal axis. Another example replaces the vertical and horizontal axes with saturation and brightness. Figure 8A The vertical axis represents saturation length (SL), but the horizontal axis represents lightness, not vector length (VL). Figure 8B The horizontal axis represents vector length (VL), but the vertical axis is replaced with saturation. Figure 8C This is an example of replacing the horizontal and vertical axes with saturation and brightness, respectively.

[0140] (2) Determine the definition and generation method of the line.

[0141] Using SL as the vertical axis and VL as the horizontal axis, color judgment is performed based on the positional relationship with the judgment line. The definition of the judgment line f(VL) is arbitrary; for example, the following definition of the judgment line f(VL) with a and b as adjustment parameters can be used.

[0142] [Formula 5]

[0143]

[0144] In order to determine the adjustment parameters a and b of Equation 5, for the two colors (e.g., black and red) before and after the change in the actual environmental detection area, various shooting conditions (external light, brightness changes caused by lighting conditions, positional relationship between the judgment object and the shooting camera, etc.) are changed and measured. The RGB values ​​of the measured colors are converted into the above VL and SL and plotted to form a judgment line that separates black and red to determine the adjustment parameters a and b.

[0145] For example, Figure 9A This is a graph that transforms the RGB values ​​of black measured under various anticipated environments into vector length (VL) and saturation length (SL), and plots them with VL as the horizontal axis and SL as the vertical axis. Figure 9B This is a graph plotted using the obtained RGB values ​​for red. Based on these graphs, a decision line 900 can be drawn to separate the black and red point groups. When expressing the decision line 900 using Equation 5, the points a and b that best approximate the curve are selected. Furthermore, in this example, as... Figure 9C The judgment line 900 shown can also be 900a.

[0146] The above describes the color judgment method for the environmental detection area. However, judging two colors is not limited to judging black and red; it can also judge two colors with clearly different saturation or brightness. For example, by adjusting the judgment line, it is also possible to judge blue and white, purple and white, red and white, black and white, green and white, brown and white, purple and pink, black and green, red and yellow, green and yellow, and orange and yellow. In addition, it is also possible to judge the color SL, which has a specified range relative to the reference point, as color 2, and to judge the color that does not belong to the specified range as not color 2. In addition, the color of the judgment result obtained in this embodiment is not a color generally defined by wavelength, but a color set in the calculation of this embodiment. In addition, it is described as color 2 here, but it can also be defined as the first color, or it can be called color (1).

[0147] Furthermore, an example was given where the color being judged was identified as one of two colors. However, the same method can be used to set multiple judgment lines to determine which of three or more colors it is. That is, to determine which of n colors it is, (n-1) judgment lines can be set in the same way to make the determination.

[0148] Therefore, in the prior art, color information changes due to changes in shooting conditions, which may affect color judgment. However, according to this embodiment, the degree of influence of shooting conditions on color judgment can be reduced, and the accuracy of color judgment can be improved.

[0149] <Judgment System>

[0150] Next, the judgment system of this embodiment that employs the above-described color judgment method will be described.

[0151] Figure 10 This is a structural diagram of the encoding tag determination system 1000. The determination system 1000 is used, for example, to read... Figure 1A , Figures 2A to 2K , Figure 3C and Figure 3F The QR code shown or Figure 2L The barcode shown in Figure 2P includes an image acquisition device 1010 for acquiring an image of the coded label, an input device 1020, an output device 1030, a data processing device 1040, and a storage device 1050, and can transmit and receive various data and signals via a signal line 1060.

[0152] The image acquisition device 1010 is a camera or similar imaging device that captures images of coded labels. It can also acquire images of stored goods, information about the goods, and the surrounding environment, in addition to the labels, as needed. After capturing the coded image, it is stored in the image data storage unit 1051 of the storage device 1050. Alternatively, the image acquisition device 1010 can also be a terminal device or device with a camera, such as a smartphone or tablet, in which case it is connected to the judgment system 1000 via wired or wireless means.

[0153] The input device 1020 is the part that receives instructions from the operator and consists of buttons, touch panels, etc.

[0154] The output device 1030 is a device that outputs (prompts) instructions to the operator, reads images, reads results, and makes judgments, and consists of a display and a communication device. This structure is standard, but it can also be configured such that some or all of the image acquisition device 1010, input device 1020, and output device 1030 are externally connected to the judgment system 1000.

[0155] Next, the storage device 1050 and the data processing device 1040 will be described in detail.

[0156] <<Storage Device 1050>>

[0157] The storage device 1050 is a part that stores various types of data and is composed of the following storage sections.

[0158] The image data storage unit 1051 is a part that stores captured images, including coded tags, input from the image acquisition device 1010.

[0159] The encoded position data storage unit 1052 is a part that stores data representing the encoded reference position identified by the encoded position recognition unit 1042 from the image data storage unit 1051 (the captured image).

[0160] The encoded data storage unit 1053 stores encoded string data (data body) that is identified by the encoded recognition unit 1043 from the image stored in the image data storage unit 1051.

[0161] The location data storage unit 1054 of the environmental detection area is a part that stores the relative location information of the environmental detection area within the code in advance (information indicating where the environmental detection area is located within the code).

[0162] The measured color data storage unit 1055 of the environmental detection area is a part that stores the color information (RGB values, etc.) extracted from the color of the environmental detection area determined by the location data storage unit 1054 of the environmental detection area.

[0163] The judgment result storage unit 1056 stores the color judgment result of the environment detection area determined by the color judgment unit 1046 (described later), the result of determining whether the environment detection area has changed color based on the color judgment result ("NG" if it has changed color / "OK" if it has not changed color), and the mark used in the screen display (described later).

[0164] The data storage unit 1057 stores data other than that processed by the data processing device 1040 (described later). Generally, when understanding changes in the environment of a product, information such as when, where, and what happened is required. Therefore, in addition to the product information stored in the coding data storage unit 1053 and the data such as temperature exceeding the range obtained from the environmental detection area stored in the judgment result storage unit 1056, it is preferable to also store the date and time of the reading process, location information, the number of the reading device (used to identify the operator), and weather information linked to the web. Furthermore, since the same reading device remains unchanged as long as it is used, the reading device number can also be added during data output (described later).

[0165] The judgment reference data storage unit 1058 stores color information of the materials / inks used in the environmental detection area before and after color development, and the relationship between the amount of environmental change and the color information of the environmental detection area (e.g., information indicating the ambient temperature corresponding to a certain color in the environmental detection area). Based on the color information of the materials / inks used in the environmental detection area before and after color development, and the relationship between the amount of environmental change and the color information of the environmental detection area, a judgment line for color judgment is calculated. Furthermore, the judgment reference data storage unit 1058 stores a judgment line for each color to be judged, and retrieves the judgment line corresponding to that color from the judgment reference data storage unit based on the color to be judged accepted as user input. Additionally, if the storage device 1050 stores the ID of the judgment object and the color information used by the judgment object in association, the used color information can be obtained based on the ID of the judgment object obtained as an image, and the color to be judged can be determined based on the color information.

[0166] <<Data Processing Device 1040>>

[0167] The data processing apparatus 1040 processes data input from the image acquisition apparatus 1010 and the input apparatus 1020, as well as data stored in the storage apparatus 1050, and outputs the results to the output apparatus 1030 or stores them in the storage apparatus 1050. It is configured with the following processing units. Furthermore, the data processing apparatus 1040 can be implemented, for example, using a computer equipped with a processing unit (CPU) and memory. The following processing units are programs stored in memory that implement these processing units, and these programs can be executed by the CPU. Alternatively, each processing unit can also be implemented using dedicated hardware.

[0168] The input control unit 1041 is responsible for classifying data input from the image acquisition device 1010 or the input device 1020 into instructions, data, etc., and transmitting them to various parts of the storage device 1050 and the data processing device 1040. In particular, it transmits image data, including the encoded environment detection area, which is the main data, to the image data storage unit 1051.

[0169] The encoded position recognition unit 1042 identifies encoded positions from image data stored in the image data storage unit 1051 and stores the recognition results in the encoded position data storage unit 1052. Image data typically consists of hundreds to thousands of points in both the horizontal and vertical directions, and no part of the image itself contains encoded data.

[0170] Therefore, by analyzing the color data of each point, the reference position of the encoding corresponds to which part of the image data. The display form and number of reference positions vary depending on the encoding standard, but are not limited to these standards. Furthermore, when multiple codes exist in the image stored in the image data storage unit 1051, the positions of multiple codes can be identified.

[0171] The encoding recognition unit 1043 uses the location data stored in the encoding location data storage unit 1052 to recognize the data body of the string recorded in the data area (unit 500) in encoded form from the image stored in the image data storage unit 1051, and stores it in the encoding data storage unit 1053.

[0172] The location determination unit 1044 of the environmental detection area determines the location of the environmental detection area 600 based on the location data stored in the encoded location data storage unit 1052 and the information stored in the encoded data storage unit 1053, such as the coordinates (X,Y) of the four corners of the QR code, and the location information stored in advance in the location data storage unit 1054 of the environmental detection area.

[0173] The measured color determination unit 1045 of the environment detection area determines the portion of the image containing the RGB value of the environment detection area 600 in the image based on the image stored in the image data storage unit 1051 and the position information of the environment detection area 600 determined by the position determination unit 1044 of the environment detection area.

[0174] The color determination unit 1046 determines which of the two predefined colors (color 1 and color 2) the color of the environmental detection area is using the method described in the above-described "Color Determination Method for Environmental Detection Area". Specifically, based on the RGB values ​​of the environmental detection area's color stored in the measured color data storage unit 767, the vector length (VL) is calculated using equation (1-4), and the saturation length (SL) is calculated using equations (1-5, 1-6, 2, 3-1, 3-2). Then, based on the relationship between the determination line (a function of VL) and SL shown in equation 5, the environmental detection area is determined to be either color 1 or color 2. Furthermore, a definition equation (equation 5) for the determination line is generated through experiments conducted beforehand under various environmental conditions and stored in the color determination unit 1046.

[0175] In addition, the color judgment unit 1046 determines, based on the color judgment result of the above-mentioned environmental detection area, whether the environmental detection area has changed color due to the rise in ambient temperature or has exceeded the predetermined upper limit temperature.

[0176] The output control unit 1047 controls the output device 1030 to output the information processed by the data processing unit 1040. Specifically, the output device 1030 outputs product information associated with the data body stored in the encoded data storage unit 1053, information such as whether the temperature exceeds the range based on the color information of the environmental detection area stored in the judgment result storage unit 1056, or reads information stored in the data storage unit 1057.

[0177] When the output target is a screen, it is preferable to output the result every time a read operation is performed. Alternatively, it is preferable to output the judgment result stored in the judgment result storage unit 1056 of the environment detection area. When the output target is a communication target, output processing can be performed every time a read operation is performed, or multiple data sets can be aggregated, or aggregated at predetermined intervals, etc.

[0178] <Processing flow of the judgment system>

[0179] Figure 11 This is a flowchart illustrating the processing flow of the judgment system 1000 in this embodiment.

[0180] First, image data including an encoding of an environmental detection area is input from the image acquisition device 1010. The input data is stored in the image data storage unit 1051 (step S1101).

[0181] Next, the encoding position recognition unit 1042 identifies the reference position of the image recognition code recorded in the image data storage unit 1051, and records the identified reference position in the encoding position data storage unit 1052. The encoding recognition unit 1043 uses the image recorded in the image data storage unit 1051 and the position data recorded in the encoding position data storage unit 1052 to determine the data area, decodes the encoding displayed in the data area, and extracts the encoded data body (string data, etc.) (step S1102).

[0182] Next, the environmental detection area location determination unit 1044 uses the location data stored in the encoded location data storage unit 1052 to determine the location of the environmental detection area in the acquired image, for example, by detecting the coordinates (X, Y) of the four corners of a QR code, for the acquired image recorded in the image data storage unit 1051. It also uses the location information of the environmental detection area stored in advance in the environmental detection area location data storage unit 1054 to determine the location of the environmental detection area in the acquired image. (Step S1103)

[0183] Next, the measured color determination unit 1045 of the environment detection area obtains the RGB values ​​of the environment detection area as color information from the acquired image based on the position information determined by the position determination unit 1044 of the environment detection area. The obtained color information (RGB values) is transmitted to the measured color storage unit 1055 of the environment detection area and stored (step S1104).

[0184] At this point, check for issues such as "overexposure" where the reference area or environmental detection area cannot be seen in the image due to reflected light when the lighting is strong, the encoded image being too small or too large, or the image being over-distorted due to an acute shooting angle. If any problems are found, return to step S1101 and perform image reading again (step S1105).

[0185] In step S1105, if the measured color data of the environmental detection area can be obtained without any problems, the color judgment unit 1046 then calculates the characteristic quantity of the color of the environmental detection area and performs color judgment based on it. Details are as described above (steps S1106, S1107).

[0186] Next, the color determination unit 1046 determines whether the environmental detection area shows color (color change) or the amount of color change based on the color determination result. Then, the data processing device 1040 determines whether the coded surrounding environment exceeds a preset benchmark (e.g., upper limit temperature) (step S1108).

[0187] The result of the color determination unit 749 is stored in the determination result storage unit 1056.

[0188] Meanwhile, the date and time of the reading process, location information, number of the reading device (used to identify the operator), weather information linked to the Web information, etc. are stored in the data storage unit 1052 (step S1109).

[0189] Then, the output device 1030 outputs information such as product information associated with the string stored in the encoded data storage unit 1053, whether the temperature exceeds the range based on the color information of the environmental detection area stored in the judgment result storage unit 1056, or reads information stored in the data storage unit 1057. When using a smartphone as the hardware of the judgment system, the output device 1030 outputs the reading results to the smartphone screen, etc. (step S1110).

[0190] Figure 12This is an example of displaying the output result of the judgment system 1000 in this embodiment, specifically the output display of the reading result on the display 1201 of the smartphone 1200. When multiple tags with QR codes that are the objects to be read are arranged side by side, multiple images can be acquired simultaneously and the analysis and processing of color changes in their environmental detection areas, etc., can be performed in parallel, and the results can be displayed side by side on the display 1201.

[0191] In addition, for Figure 11 The result determined by step S1108 in the flowchart is displayed on the display 1201 using AR (Augmented Reality) with an "×" symbol 1202a indicating that the temperature is out of range (NG) or a "check mark" symbol 1202b indicating that the temperature is within range (OK), thereby making it easy for operators to identify the result.

[0192] Furthermore, the smartphone 1200 can be used not only as an output device for the judgment results but also as an image acquisition device 1010. In this case, after all QR codes have been read, touching the scan completion button 1203 allows the user to view the judgment results for all read QR codes on the smartphone screen 1201 and also allows the image to be sent to a specified address.

[0193] Alternatively, the judgment system 1000 in this embodiment can be constituted by a general-purpose smartphone 1200 equipped with a camera, screen, and communication device. Alternatively, a terminal device or wireless terminal such as a general-purpose smartphone 1200 can be used in addition to the judgment system 1000. In this case, the image acquired by the smartphone 1200 can be sent to the judgment system 1000, the smartphone 1200 can obtain the judgment result from the judgment system 1000, and output the judgment result from the smartphone 1200.

[0194] Figure 13 This is an example of the display of input information for the judgment system 1000 in this embodiment. For example, it can be obtained by photographing the barcode of the judgment object, as shown in the screen display 1301 of the smartphone 1200. The information at the time of photographing can be obtained by the smartphone 1200 as shown in 1302, but it is not limited to this. It can also be input by the user, obtained by a drop-down method, or obtained in accordance with the photographing situation.

[0195] Based on the above-described embodiment, a judgment system can be provided that can accurately determine the color of an environmental detection area in a data area that has an environmental detection area whose color changes due to environmental changes, and which uses existing QR code or barcode encoding labels, without needing to set a reference area to correct for color information differences caused by shooting conditions. Furthermore, in existing barcodes that have a reference area, a reference area of ​​a certain size needs to be configured in order to read the reference area, such as... Figure 17A In the three lookahead patterns 300a-300c shown, the method of configuring the reference area has the problem of difficulty in reducing the size of the barcode. According to this embodiment, since color can be determined without setting a reference area, a judgment system can be provided even for barcodes smaller than existing barcodes, such as... Figure 17B , 17C As shown, the label size can be reduced to 1 / 4 to 1 / 3 compared to existing methods. The sum of the long and short sides of the label, such as the barcode, can be, for example, less than 40 mm. Furthermore, while multi-colored inks were previously required to be printed in the reference area, this embodiment eliminates the need for printing in the reference area, enabling a system for judging monochrome barcodes. Additionally, a reading system that allows for easy color judgment can be provided.

[0196] Based on the above, it is possible to expand the range of products to which barcodes can be attached and to properly manage product temperature during distribution.

[0197] Example 2

[0198] Figure 14 This is a diagram illustrating the outline of an information processing system 1400 using a judgment system 1000 as a second embodiment of the present invention. The information processing system 1400 includes an information processing device 1410 and a smartphone 1200, which is the judgment system 1000 of Embodiment 1, and the smartphone 1200 is configured at various locations during the product distribution process.

[0199] Figure 14In this example, the smartphone 1200 is configured in various locations including collection, output warehouses, customs clearance warehouses, input warehouses, and consumer locations. The information processing device 1410, capable of judging color changes in the environmental detection area included in the QR code 1420, comprises an input unit 1411, a storage unit 1412, an information processing unit 1413, and an output unit 1414. The input unit 1411 is the part that inputs information output from the smartphone 1200. The storage unit 1412 is the part that accumulates and stores information output from the smartphone 1200. The storage unit 1412 is a non-temporary or temporary recording medium that stores various programs and data. Examples of storage units for the storage unit 1412 include ROM (Read Only Memory), RAM (Random Access Memory), HDD (Hard Disk Drive), and flash memory.

[0200] The information processing unit 1413 is responsible for organizing and analyzing the information accumulated in the storage unit 1412, and is implemented by the CPU (Central Processing Unit). For example, by performing statistical analysis on information from the smartphone 1200, it is possible to determine when, what personnel, and in what location caused the temperature to exceed the range, which can help improve business operations.

[0201] The output unit 1414 is the part that transmits the information processed by the information processing unit 1413 to the necessary locations. When the information processing device 1410 has a display, it can output the processing results to that display.

[0202] The following illustrates an example of applying the information processing system 1400 to the distribution process from production to consumption. For example, the information processing system 1400 enables consumers who receive the product to know physical quantities such as ambient temperature during the distribution of the product, such as wine. For instance, if the product is wine, a QR code 1420 is displayed on a label attached to the wine, the box containing the wine, etc.

[0203] The information processing system 1400 includes a smartphone 1200, which serves as a judgment system 1000 for QR code 1420, and an information processing device 1410. The smartphone 1200 (input / output device) uploads the information obtained and analyzed by the judgment system 1000 for QR code 1420 to the information processing device 1410 during product circulation. Figure 14 Examples include a smartphone 1200 (input / output device) that can perform input and output using a single terminal, but dedicated input and output devices such as image capture devices can also be used.

[0204] During product pickup, the person in charge of product transportation (e.g., the driver) uses a smartphone 1200 (input / output device) to photograph the QR code 1420 marked on the product. Input information, including the image of the QR code 1420, is then uploaded to the information processing device 1410. The QR code 1420 and the judgment system 1000 are used to determine whether the temperature exceeds the range during reading.

[0205] At this point, product identification information (item identification information), as well as the shooting time and location, are also uploaded as input. Item identification information includes, for example, GTIN (Global Trade Item Number), EAN (European Article Number), and UPC (Universal Product Code). Information about the item, such as the manufacturer, seller, manufacturing date, and expiration date, is preferably associated with the item identification information.

[0206] Similarly, the personnel in the output warehouse, customs clearance warehouse, and input warehouse use their smartphones 1200 (input / output devices) to photograph the QR codes 1420 marked on the products. This input information is then uploaded to the information processing device 1410. The information processing device 1410 then determines, based on the uploaded input information, whether the temperature exceeds the acceptable range during reading.

[0207] On the other hand, consumers (users) use smartphones 1200 (input / output devices) to read the product's QR code 1420, thereby accessing the URL (website) stored in the QR code 1420. For example, a dedicated application running on the smartphone 1200 (input / output device) can be used to perform the reading.

[0208] In addition, in this embodiment, the smartphone 1200 includes a judgment system 1000, but is not limited thereto. The smartphone 1200 may also be a dedicated reader as an input device, a personal computer as an output device, etc.

[0209] According to the embodiment described above, it is possible to track the environmental conditions of the distributed product during the distribution process from production to consumer, and if a defect is found in the distributed product when it reaches the consumer, it is possible to find out where the problem occurred during the distribution process.

[0210] Example 3

[0211] Figures 15A to 15Dshows the actual analysis results. Color judgment of black and red was performed for the black environment detection area and the red environment detection area under 12 modes of imaging conditions. At this time, the judgment line uses Equation 5, with a set to 20 and b set to 0.09. In addition, the imaging conditions at the time of judgment are shown in Table 1.

[0212] [Table 1]

[0213]

[0214] Here, Figure 15A is the judgment result when imaging is performed using a portable terminal manufactured by Company A, Figure 15B is the judgment result when imaging is performed using a portable terminal manufactured by Company B, Figure 15C is the judgment result when imaging is performed using a portable terminal manufactured by Company C, Figure 15D is the judgment result when imaging is performed using a portable terminal manufactured by Company D. In addition, * indicates that the judgment result is black, and ○ indicates that the judgment result is red.

[0215] Further, in the case of the present example, with respect to the judgment line, an area where SL≥a / VL+b is satisfied is judged as red, and an area where SL<a / VL+b is satisfied is judged as black. As a result, when performed using 4 types of portable terminals, black and red can be judged with an accuracy of 98%. Therefore, in the present example, colors can be judged with good accuracy even when the code does not include a reference area.

[0216] Example 4

[0217] Figure 16 shows the actual analysis results. Color judgment of white and blue was performed for the white environment detection area and the blue environment detection area under 12 modes of imaging conditions. At this time, the judgment line is y=ax+b, with a set to 0.0012 and b set to -0.22. In addition, the imaging conditions at the time of judgment are shown in Table 1. In addition, Figure 16 is the judgment result when imaging is performed using a portable terminal manufactured by Company C. In addition, * indicates that the judgment result is blue, and ○ indicates that the judgment result is white.

[0218] Further, in the case of the present example, with respect to the judgment line, an area where SL≥a×VL+b is satisfied is judged as blue, and an area where SL<a×VL+b is satisfied is judged as white. This judgment result can judge blue and white with an accuracy of 98% or higher. Therefore, in the present example, for colors other than black and red, colors can be judged with good accuracy even when the code does not include a reference area.

[0219] Description of Reference Signs in Drawings

[0220] 100: Label / Identification Item; 200: QR Code; 201: Data Matrix Code; 210: One-Dimensional Code; 300a: Finder Pattern (Location Pattern); 300b: Finder Pattern (Location Pattern); 300c: Finder Pattern (Location Pattern); 310: First Finder Pattern Area; 320: Second Finder Pattern Area; 330: Third Finder Pattern Area; 400: Correction Pattern; 410: First Correction Pattern Area; 420: Second Correction Pattern Area; 430: Third Correction Pattern Area; 500: Unit (Data Area); 600: Environmental Detection Area; 1000: Judgment System; 1010: Image Acquisition Device; 1020: Input Device; 1030: Output Device; 1040: Data Processing Device; 1041: Input Control Unit; 1042: Encoding Position Recognition Unit; 1043: Encoding Recognition Unit; 1044: Ring... 1045: Location determination unit for the environmental detection area; 1046: Measured color determination unit for the environmental detection area; 1047: Color judgment unit; 1050: Output control unit; 1051: Storage device; 1052: Image data storage unit; 1053: Encoded location data storage unit; 1054: Location data storage unit for the environmental detection area; 1055: Measured color data storage unit for the environmental detection area; 1056: Judgment result storage unit; 1057: Read data storage unit; 1058: Judgment reference data storage unit; 1060: Signal line; 1200: Smart phone (portable terminal); 1400: Information processing system; 1410: Information processing device; 1411: Input unit; 1412: Storage unit; 1413: Information processing unit; 1414: Output unit.

Claims

1. A judgment system for judging the color of an object, characterized in that, include: A storage device that stores a judgment line with the brightness and saturation of the color of the judgment object as parameters; and A data processing device that acquires color information of the object to be judged and judges the color of the object to be judged based on the color information; The data processing device includes: The color judgment unit calculates the characteristic quantity of the lightness of the color information in the color space, i.e., the vector length of the color information, and the characteristic quantity of the saturation of the color information, i.e., the vector direction of the color information, and compares them with the judgment line to determine the color of the judgment object.

2. The judgment system as described in claim 1, characterized in that: The color of the object being judged is one of several predefined colors with different brightness or saturation.

3. The judgment system as described in claim 1, characterized in that: The data processing device includes a measured color determination unit, which acquires an image of the color of the object to be judged and obtains the color information of the object to be judged based on the image.

4. The judgment system as described in claim 3, characterized in that: The measured color determination unit obtains the RGB values ​​as the color information of the object to be determined. The color judgment unit calculates the RGB vector length (VL) and the direction (SL) of the RGB vector in three-dimensional polar coordinates based on the obtained RGB values, plots the SL and VL as the vertical and horizontal axes respectively, and makes color judgments based on their positional relationship with the judgment line.

5. The judgment system as described in claim 4, characterized in that: If the calculated VL and SL are located within a specified area relative to the judgment line, the color judgment unit determines that it is a pre-defined first color; if the calculated VL and SL are not located within the specified area relative to the judgment line, it determines that it is not a pre-defined first color.

6. The judgment system as described in claim 4, characterized in that: The color judgment unit uses lightness instead of VL and saturation instead of SL to perform color judgment.

7. The judgment system as described in any one of claims 1 to 6, characterized in that: It includes an image acquisition device that acquires an image of the color of the object to be determined.

8. The judgment system as described in claim 7, characterized in that: The color of the object to be judged is black and red, or blue and white, or purple and white, or red and white, or black and white, or green and white, or brown and white, or purple and pink, or black and green, or red and yellow, or green and yellow, or orange and yellow.

9. A color judgment method for judging the color of an object, characterized in that, include: The color information acquisition step acquires the color information of the object being judged. and The data processing step determines the color of the object to be judged based on the color information obtained in the color information acquisition step. The data processing steps include: The color judgment step calculates the characteristic quantity of the lightness of the color information in the color space, i.e., the vector length of the color information, and the characteristic quantity of the saturation of the color information, i.e., the vector direction of the color information, and compares them with the judgment line with the lightness and saturation of the color of the judgment object as parameters, thereby judging the color of the judgment object.

10. The color determination method as described in claim 9, characterized in that: The color of the object being judged is one of several predefined colors with different brightness or saturation.

11. The color determination method as described in claim 9, characterized in that: The data processing steps include a measured color determination step, which obtains an image of the color of the object to be judged and obtains the color information of the object to be judged based on the image.

12. The color determination method as described in claim 11, characterized in that: The measured color determination step includes the step of obtaining RGB values ​​as color information of the color of the object to be determined; The color judgment step calculates the RGB vector length (VL) and the direction (SL) of the RGB vector in three-dimensional polar coordinates based on the RGB values ​​obtained in the measured color determination step. The SL and VL are plotted as the vertical axis and the horizontal axis, respectively, and the color is judged according to the positional relationship with the pre-defined judgment line.

13. The color determination method as described in claim 12, characterized in that: The color determination step uses lightness instead of VL and saturation instead of SL to determine the color.

14. The color determination method according to any one of claims 9 to 13, characterized in that: The color of the object to be judged is black and red, or blue and white, or purple and white, or red and white, or black and white, or green and white, or brown and white, or purple and pink, or black and green, or red and yellow, or green and yellow, or orange and yellow.

15. A program that enables a computer to perform the function of a data processing device that acquires color information of multiple judgment objects with different brightness and saturation, and judges the color of the judgment objects based on the color information, characterized in that: The procedure described: The characteristic quantity of lightness (i.e., the vector length of the color information) and the characteristic quantity of saturation (i.e., the vector direction of the color information) in the color space are calculated and compared with the judgment line that takes the lightness and saturation of the color of the judgment object as parameters, thereby judging the color of the judgment object.

16. An information processing system, characterized in that: Includes a terminal device and an information processing device as the judgment system as described in claim 1. The terminal devices are configured in multiple locations throughout the distribution process of the specified products. Multiple terminal devices detect color changes in the environmental detection area of ​​the coded label of the product during each distribution process, thereby determining whether environmental changes have occurred in the product during each distribution process. The information processing device collects information from multiple terminal devices regarding whether there are environmental changes in the circulating products during each circulation process and provides prompts to the user.

17. A terminal device capable of communicating with the judgment system as described in claim 1, characterized in that: The terminal device acquires an image of the color of the object to be judged, sends the image to the judgment system, receives the judgment result from the judgment system, and outputs the judgment result.

18. A label or marker capable of determining color using the determination system as described in claim 1, characterized in that: The label includes an environmental detection area whose color changes with environmental variations. The judgment system obtains the color information of the environmental detection area.

19. The label as described in claim 18, characterized in that: The sum of the long and short sides of the label is less than 40 mm.

Images