Method for creating data for Anti-counterfeit printed matter and software for creating data for Anti-counterfeit printed matter

Abstract

To provide a method for creating data for anti-counterfeit printed matter and software for creating the same, which can enhance color reproducibility including halftone representation of visible images, thereby allowing practical use of fine images having gradation such as face photos and landscape paintings.SOLUTION: A method for creating data for anti-counterfeit printed matter includes a visible image formed by an ink without infrared-absorbing dye and an invisible image formed by an ink with infrared-absorbing dye, the method comprising: a process of converting density-corrected image data, which is obtained by density correction of first image data corresponding to a base image of the visible image, into a chromatic color so that the density-corrected image data is prevented from being converted into black (K); and a process of performing color conversion by reflecting a color property of the first image data to generate color-converted image data.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] This invention relates to a method and software for creating data for anti-counterfeit printed matter that can be easily authenticated using a discriminator to prevent the counterfeiting and tampering of passports, various certificates, important documents, etc., and that can be applied to various types of cards, passports, certificates, etc. [Background technology]

[0002] It is important to provide high security to printed materials such as passports, various certificates, and important documents by providing them with anti-counterfeit and anti-tampering properties. A common method for providing these printed materials with anti-counterfeit and anti-tampering properties is to apply some means and effect to the printed material to create an invisible image that cannot be recognized by the naked eye. Typical examples include applying functional ink that prevents colors from being reproduced correctly in color copiers, and applying copy-protection lines to printed materials that cannot be reproduced by copying.

[0003] However, in recent years, the performance of color copiers has improved, resulting in improved copy resolution and image reproducibility, which has reduced the effectiveness of copy prevention lines. Furthermore, the use of functional inks, such as fluorescent inks, which are invisible to the naked eye under normal light, on printed materials has also been reduced in its effectiveness as a deterrent to counterfeiting, as fluorescent ink materials are now commercially available and readily available to anyone.

[0004] In order to solve this problem, the applicant has applied for a line print, which is a measure to prevent counterfeiting by copying using a high-resolution copier without using special ink, and which allows a gradation image to be seen when viewed with the naked eye under normal light, and a different gradation image to be seen when viewed using a discriminating tool such as an infrared camera or IR (Infrared) viewer (see, for example, Patent Document 1).

[0005] The applicant has also filed a patent application for an anti-counterfeiting printed matter that forms visible and invisible image areas without using a special screen (see, for example, Patent Document 2). More specifically, in an area where an invisible image is formed using black (K) ink containing an infrared absorbing pigment, the density of the invisible image is subtracted from the visible image formed using cyan (C), magenta (M), and yellow (Y) inks that do not contain infrared absorbing pigment, thereby making the invisible image invisible.

[0006] With this invention, when using an expensive production printer, the image signals of cyan (C), magenta (M) and yellow (Y) that make up the visible image, and the image signal of black (K) that makes up the invisible image are input into the printer, and the visible image is printed directly using cyan (C), magenta (M) and yellow (Y) inks, and the invisible image is also printed using black (K) ink, making it possible to print out anti-counterfeit printed material.

[0007] However, in order to accommodate the large differences in ink hues and other characteristics between manufacturers, commonly used home printers, when image signals for cyan (C), magenta (M), and yellow (Y), as well as the black (K) image signal that constitutes the invisible image, are input to the printer, the built-in printer driver first converts them into RGB image signals, which have a wider color reproduction range, and then converts them again into image signals for cyan (C), magenta (M), and yellow (Y) before printing.

[0008] In this process, when the input cyan (C), magenta (M), and yellow (Y) image signals are converted into RGB image signals, the black (K) image signal, which contains the infrared-absorbing pigment that makes up the invisible image, is lost. Furthermore, in the process of converting the RGB image signals into cyan (C), magenta (M), and yellow (Y) image signals, the printer driver often uses black (K) ink in areas where the three colors overlap. This makes it impossible to accurately distinguish and print the visible and invisible images as intended, resulting in a situation where the visible and invisible images cannot be reproduced as intended. As a result, it has been impossible to print anti-counterfeit printed materials using ordinary home printers.

[0009] Therefore, the applicant of the present application has filed an application for an invention relating to an anti-counterfeit printed matter that can be printed out with good quality not only by expensive production printers but also by ordinary home printers (see, for example, Patent Document 3).

[0010] In this invention, before the printer finally prints out the cyan (C), magenta (M), yellow (Y), and black (K) signals, an RGB image signal is used to form a visible image using pixels having only one of the following colors: pseudo red (R) obtained by multiplying magenta (M) and yellow (Y), pseudo green (G) obtained by multiplying cyan (C) and yellow (Y), or pseudo blue (B) obtained by multiplying cyan (C) and magenta (M), i.e., 100% density pseudo red (R), 100% density pseudo green (G), or 100% density pseudo blue (B), and an invisible image is formed using black (K) pixels, thereby avoiding the situation where the three colors cyan (C), magenta (M), and yellow (Y) overlap in the same area in the visible image region and are converted to black (K) by the printer driver.

[0011] However, according to this invention, the color of the pixels that make up the visible image is limited to one of 100% density pseudo red (R), 100% density pseudo green (G), or 100% density pseudo blue (B). Therefore, there is a problem that the intermediate tones (gradation area ranging from 100% density to 0%) of pseudo red (R), pseudo green (G), pseudo blue (B), or cyan (C), magenta (M), and yellow (Y) are lost, resulting in a narrow color expression range and poor color reproducibility. [Prior art documents] [Patent documents]

[0012] [Patent Document 1] Patent No. 3544536 [Patent Document 2] Japanese Patent Publication No. 2022-123294 [Patent Document 3] Japanese Patent Publication No. 2022-146971 Summary of the Invention [Problem to be solved by the invention]

[0013] In view of the above circumstances, the present invention aims to provide a method and software for creating data for anti-counterfeit printed matter that can be produced without using special inks, regardless of the model, performance or manufacturer of the printer, in which a visible image is visible when observed with the naked eye under normal light and an invisible image is visible when observed under infrared light irradiation, and that can in particular improve the color reproducibility including halftones of the visible image and enable the practical use of beautiful images with gradations such as portraits and landscape paintings. [Means for solving the problem]

[0014] The method for creating data for anti-counterfeit printed matter of the present invention is a method for creating data for anti-counterfeit printed matter in which at least a portion of the printing area of a substrate is provided with a visible image formed with ink that does not contain infrared-absorbing pigment, and an invisible image formed with ink that does contain infrared-absorbing pigment, and the visible image and invisible image share some of the same areas.The creation method is characterized by comprising the steps of: acquiring first image data corresponding to the original image of the visible image and second image data corresponding to the original image of the invisible image; generating density-corrected image data of the visible image by correcting the density so that the minimum density value of the area in the first image data that is not shared with the invisible image becomes the maximum density value of the second image data; converting the density-corrected image data of the visible image into a chromatic color that will not be converted to black (K); generating color-converted image data of the visible image using color conversion processing that reflects the color of the first image data; and combining the color-converted image data of the visible image with the second image data.

[0015] In addition, the method of creating data for anti-counterfeit printed matter of the present invention is characterized in that when the invisible image is a gradation image with partially different densities, the step of generating density-corrected image data corrects the density of each pixel of the first image data in the area shared with the invisible image from the density of the pixel of the second image data corresponding to each pixel of the first image data to a range of 100% density.

[0016] Furthermore, in the method for creating data for anti-counterfeit printed matter of the present invention, in the color conversion processing step, a pseudo RGB pattern consisting of pseudo red (R), pseudo green (G), and pseudo blue (B) is used in which each pixel constituting the density-corrected image data has a predetermined red (R), green (G), and blue (B) value that will not be converted to black (K), and when the position of each pixel constituting the density-corrected image data is expressed as (x, y), the red (R) value of each pixel of the density-corrected image data before the color conversion processing is converted to black (K). 1(x,y) ), Green (G 1(x,y) ) and Blue (B 1(x,y) ) and the pseudo red (R 2(x,y)), pseudo green (G 2(x,y) ) and pseudo blue (B 2(x,y) ) and the pseudo red (R (x,y) ), pseudo green (G (x,y) ) and pseudo blue (B (x,y) ) and the following relationship is satisfied: Formula (I)R (x,y) =R 2(x,y) +R 1(x,y) ·(255-R 2(x,y) ) / 255; Formula (II)G (x,y) =G 2(x,y) +G 1(x,y) ·(255-G 2(x,y) ) / 255; Formula (III)B (x,y) =B 2(x,y) +B 1(x,y) ·(255-B 2(x,y) ) / 255;

[0017] Furthermore, software for creating data for anti-counterfeit printed matter of the present invention is characterized in that it causes a computer to execute any one of the above-mentioned methods for creating data for anti-counterfeit printed matter. [Effects of the Invention]

[0018] According to the present invention, it is possible to obtain good print quality without relying on a printer, in terms of the concealment of invisible images when observed with the naked eye under normal light, the visibility of invisible images when observed under infrared light irradiation, and the clarity of visible images, and in particular, it is possible to improve the color reproducibility including half-tones of visible images, and it is possible to provide a method and software for creating data for anti-counterfeit printed materials that enables the practical use of beautiful images with gradations such as portraits and landscape paintings. [Brief explanation of the drawings]

[0019] [Figure 1] 10 is a diagram showing that a visible image and an invisible image are created to share the same area in an anti-counterfeit printed matter created by the method for creating data for anti-counterfeit printed matter of the present invention. FIG. [Figure 2] 1 is a block diagram showing the configuration of an apparatus for creating data for anti-counterfeit printed matter according to an embodiment of the present invention; [Figure 3] 3 is a flowchart showing the steps of a method for creating data for anti-counterfeit printed matter according to an embodiment of the present invention. [Figure 4] 10A and 10B are diagrams showing original image data and a density histogram of a visible image, and original image data and a density histogram of an invisible image; [Figure 5] FIG. 10 is a diagram showing a density-corrected image obtained by adjusting the density of original image data of an invisible image. [Figure 6] 10A and 10B are diagrams illustrating the background part of the visible image to which density correction is performed in step S12. [Figure 7] FIG. 10 is a diagram showing visible image correction data generated in step S12. [Figure 8] FIG. 10 is a diagram showing the configurations of pseudo blue (B), pseudo green (G), and pseudo red (R) used in the color conversion in step S13. [Figure 9] FIG. 10 is a diagram showing corrected visible image data before color conversion in step S13. [Figure 10] FIG. 10 is a diagram showing color-converted visible image data that has been color-converted in step S13 and converted into chromatic colors. [Figure 11] 10A and 10B are diagrams illustrating a process of combining color-converted visible image data after color conversion with a density-corrected image of an invisible image. [Figure 12] 10 is a flowchart showing the steps of a method for creating data for anti-counterfeit printed matter according to a second embodiment of the present invention. [Figure 13] 10A and 10B are diagrams showing an example of original image data and a density histogram of an invisible image in the second embodiment. [Figure 14] FIG. 10 is a diagram showing a density-corrected image obtained by adjusting the density of original image data of an invisible image in the second embodiment. [Figure 15] 10 is a diagram showing an area to be density corrected and density-corrected visible image correction data in step S12 of the second embodiment. FIG. [Figure 16]FIG. 10 is a diagram schematically showing the process of combining color-converted visible image data with a density-corrected image of an invisible image in step 31 of the second embodiment. [Figure 17] FIG. 10 is a diagram illustrating another example of an invisible image according to the second embodiment. [Figure 18] 10A and 10B are diagrams illustrating examples of two pixels to be subjected to density correction in step S12 of the second embodiment. [Figure 19] FIG. 10 is a diagram showing density histograms of two pixels subjected to density correction in step S12 of the second embodiment. [Figure 20] FIG. 10 is a diagram showing corrected visible image data subjected to density correction in step S12 of the second embodiment. [Figure 21] FIG. 10 is a diagram schematically showing the process of combining color-converted visible image data with a density-corrected image of an invisible image in step 31 of the second embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0020] An apparatus, method, and software for creating data for anti-counterfeit printed matter according to an embodiment of the present invention will be described below with reference to the drawings. This data creating apparatus, method, and software creates a visible image using, as a base image, a color image with continuous gradations, such as a face image related to personal information, and also creates an invisible image using, as a base image, any image, such as letters, numbers, symbols, figures, marks, designs, patterns, face images, or landscape images, that are somehow related to the personal information, and then performs density correction and color conversion processing, as described below, to synthesize the images to create data for anti-counterfeit printed matter.

[0021] 1(a) shows an example of an anti-counterfeit printed matter (21) produced by applying a method for creating data for an anti-counterfeit printed matter according to one embodiment of the present invention. This anti-counterfeit printed matter (21) has a visible image (11) and an invisible image (12) formed in at least a portion of the printing area on a substrate (22).

[0022] The visible image (11) is, for example, a color image capable of having continuous gradations suitable for a facial image or the like, or is not limited to a facial image and may be any image such as letters, numbers, symbols, figures, marks, designs, patterns, landscape images, etc., formed in at least a part of the printing area. In this embodiment, an example of the visible image (11) will be described, in which a "facial image" having continuous gradations as shown in Fig. 1(b) is used.

[0023] The invisible image (12) is an image intended to be visible when irradiated with infrared light, and may include any image, such as letters, numbers, symbols, figures, marks, designs, patterns, facial images, or landscape images, and is formed in at least a portion of the printing area. At least a portion of the invisible image (12) and at least a portion of the visible image (11) are formed so as to share the same area. In this embodiment, an example of the invisible image (12) will be described, in which the letter "A" having a certain density as shown in FIG. 1(c) is used. In the present invention, "at least a portion of the invisible image (12) and at least a portion of the visible image (11) sharing the same area" means, for example, that the area of the "facial image" in the visible image (11) and part of the letter "A" in the invisible image (12) are formed in the same area, as shown in FIG. 1(a). The letter "A" may be formed within the area of the "facial image," or part of the letter "A" may be formed outside the area of the "facial image."

[0024] Such visible image (11) and invisible image (12) are combined in the printing area to form an anti-counterfeit printed matter (21). As will be described later, the invisible image (12) has a predetermined density, for example, 10% (gray level 229) or 20% (gray level 204), and the background portion of the visible image (11) where the invisible image (12) is not present similarly has a predetermined density or more, for example, 10% (gray level 229) or 20% (gray level 204) or more. As a result, the anti-counterfeit printed matter (21) has an overall density of a predetermined density, for example, 10% (gray level 229) or 20% (gray level 204) or more.

[0025] (Device for creating data for anti-counterfeit printed materials) 2 shows the configuration of a device (M) for creating data for anti-counterfeit printed matter according to one embodiment of the present invention. The device (M) for creating data for anti-counterfeit printed matter according to this embodiment comprises an input means (M1), an editing means (M2), a display means (M3), an output means (M4), a communication interface (M5), a database (M6), and a storage means (M7).

[0026] The communication interface (M5) connects a computer terminal connected to a network (not shown) with the device (M) for creating data for anti-counterfeit printed matter.

[0027] The database (M6) stores in advance image data corresponding to the original images of the visible image (11) and the invisible image (12).

[0028] The input means (M1) includes a visible image input means (M1a) and an invisible image input means (M1b).

[0029] The visible image input means (M1a) inputs desired image data via a communication interface (M5) or inputs image data previously stored in a database (M6), thereby acquiring base image data corresponding to the base image of the visible image (11).

[0030] The invisible image input means (M1b) inputs the desired image data via the communication interface (M5) in the same manner as the visible image input means (M1a), or inputs image data that has been previously stored in the database (M6), thereby obtaining base image data corresponding to the base image of the invisible image (12).

[0031] The editing means (M2) includes an output level adjusting means (M2a), a grayscale image converting means (M2b), a color converting means (M2c), and a combining means (M2d).

[0032] The output level adjustment means (M2a) adjusts the output level and performs density correction on the base image data corresponding to the base image of the visible image (11) acquired by the input means (M1) and the base image data corresponding to the base image of the invisible image (12).

[0033] The grayscale image conversion means (M2b) converts the original image data corresponding to the original image of the invisible image (12) input by the invisible image input means (M1b) into an RGB image or a monochrome binary image into an 8-bit grayscale image. For example, if the original image of the invisible image (12) is a color image, the grayscale image conversion means (M2b) converts it into a grayscale image having continuous black and white gradations that can be printed using black (K) containing an infrared absorbing dye.

[0034] The color conversion means (M2c) performs color conversion on the visible image containing achromatic colors using a pseudo RGB pattern to obtain a visible image in which all colors are chromatic.

[0035] The synthesizing means (M2d) synthesizes the invisible image with the visible image, which has been color-converted to be entirely chromatic and contains halftones.

[0036] The display means (M3) displays on a monitor the image input by the input means (M1) and the image edited by the editing means (M2).

[0037] The output means (M4) is a production printer such as a color laser printer or a general home printer such as a color inkjet printer, and is given image data in which a visible image and an invisible image are combined by the editing means (M2) and printed out.

[0038] The storage means (M7) stores image data input by the input means (M1), the communication interface (M5) and the database (M6), and stores data necessary for processing by the editing means (M2), processed data, etc.

[0039] (Method for creating data for anti-counterfeit printed materials) FIG. 3 shows the procedure of a method for creating data for anti-counterfeit printed matter using the device (M) for creating data for anti-counterfeit printed matter shown in FIG.

[0040] In step S11, the visible image input means (M1a) acquires base image data corresponding to the base image of the visible image (11). In the present invention, the format of the base image data acquired by the visible image input means (M1a) is not particularly limited as long as it is image data that can process RGB values, and image data in formats such as bitmap, JPEG, and TIFF may be acquired.

[0041] In step S12, the output level adjustment means (M2a) adjusts the output level of the base image data corresponding to the base image of the acquired visible image (11). The area for adjusting the output level in step S12 differs depending on whether the invisible image (12) is composed of a constant density or whether the invisible image (12) has gradations in density, and the details of the process will be described later.

[0042] In step S13, color conversion is performed on the density-corrected visible image 11. The details of this process will be described later.

[0043] In step S21, the invisible image input means (M1b) acquires base image data corresponding to the base image of the invisible image (12). In the present invention, the base image data acquired by the invisible image input means (M1b) may be any of an RGB image, a monochrome binary image, and a grayscale image, and image data in a format such as bitmap, JPEG, or TIFF is acquired.

[0044] In step S22, the grayscale image conversion means (M2b) converts the original image data corresponding to the original image of the acquired invisible image (12) into a grayscale image as needed. For example, if the original image data corresponding to the original image of the invisible image (12) acquired by the invisible image input means (M1b) is an RGB image or a monochrome binary image, the grayscale image conversion means (M2b) converts it into a grayscale image. The process of converting the original image into a grayscale image by the grayscale image conversion means (M2b) can be performed using, for example, the mode conversion processing function of Photoshop (registered trademark), which is image processing software manufactured by Adobe (registered trademark). Note that if the original image data acquired by the invisible image input means (M1b) is a grayscale image (8 bit), the process of step S22 does not need to be performed.

[0045] In step S23, the output level adjustment means (M2a) adjusts the output level of the base image data corresponding to the base image of the acquired invisible image 12, as necessary. The process of adjusting the output level of the base image data in step S23 can be performed, for example, by setting a predetermined tone curve using a tone curve change function of Photoshop (registered trademark), which is image processing software made by Adobe (registered trademark).

[0046] In step S31, the image data color-converted for the visible image (11) in step S13 is combined with the image data in which the output level of the base image of the invisible image (12) has been adjusted in step S23, or the base image data of the invisible image (12) (if step S23 is not performed), and the combined result is output as image data for the anti-counterfeit printed matter (21).

[0047] (First embodiment) The first embodiment is a method for creating data for anti-counterfeit printed matter when the invisible image (12) is configured with a constant density. The following describes the detailed processing content of each step. Here, an example is described in which, in step S11, base image data (11A) corresponding to the base image of the visible image (11) shown in FIG. 4(a) is acquired in the format of a TIFF image, and in step S21, base image data (12A) corresponding to the base image of the invisible image (12) shown in FIG. 4(b) is acquired in the form of a grayscale image. Note that FIG. 4(c) is a density histogram of the base image data (11A) corresponding to the base image of the visible image (11). Here, an example is described in which an image with a density ranging from 0% (gray level 255) to 100% (gray level 0) is acquired. Also, FIG. 4(d) is a density histogram of the base image data (12A) corresponding to the base image of the invisible image (12). Here, an example is described in which an image with a constant density of 50% (gray level 127) is acquired.

[0048] (Density correction of invisible image step S23) First, the details of the process of adjusting the output level of the base image data (12A) corresponding to the base image of the invisible image (12) by the output level adjustment means (M2a) in step S23 will be described. Note that the method of creating data for anti-counterfeit printed matter of the present invention does not require the process of step S23, and it may be omitted if the density of the base image data (12A) acquired in step S21 has the configuration described below. Also, in this embodiment, since the base image data (12A) acquired in step S21 is an example of a grayscale image, there is no need to perform the process of converting the base image data (12A) to a grayscale image by the grayscale image conversion means (M2a) in step S22.

[0049] Step S23 is a process for adjusting the density of the invisible image (12) when printed in at least a portion of the printing area on the substrate (22) by adjusting the output level of the base image data (12A) corresponding to the invisible image (12).

[0050] 5 shows a density-corrected image (12B) obtained by adjusting the density of the original image data (12A) in step S23, as well as the original image data (12A) before the density adjustment and their density histograms for comparison. In the density histogram of the original image data (12A) before the density adjustment shown in FIG. 5(c), as mentioned above, the entire character "A" is an image with a constant density at 50% density (gray level 127).

[0051] The maximum density of the density-corrected image (12B) whose density has been adjusted in step S23 varies depending on the desired configuration of the anti-counterfeit printed matter (21) to be produced. For example, if an image with rich gradations is to be produced, the maximum density of the density-corrected image (12B) corresponding to the invisible image is preferably about 20%. If the maximum density exceeds 20%, the anti-counterfeit printed matter (21) will have a strong black cast, and the reproducibility of the highlights in the image will be poor. Conversely, if an image with an overall black cast is to be produced, the maximum density can be set in the range of 20% to 75%. If the maximum value is set to 76% or higher, the gradations of the visible image (11) will become indistinguishable due to the black cast, resulting in an image that is entirely black.

[0052] The minimum density of the invisible image (12) can be set from 0%, but preferably set to around 10%, which allows the invisible image (12) to be clearly observed when the anti-counterfeit printed matter (21) is viewed with an identification tool (infrared camera, IR viewer). Note that the greater the difference between the set maximum and minimum density values, the richer the gradation of the invisible image (12) will be, but the more black the anti-counterfeit printed matter (21) will have. Therefore, it is necessary to set the maximum and minimum density values based on an idea of the type of image the anti-counterfeit printed matter (21) will have.

[0053] Here, as shown in FIG. 5(d), an example will be described in which the image is converted into an image with a density of 20% (gray level 204) by performing density adjustment in step S23.

[0054] The output level of the original image data (12A) can be adjusted by a general image processing method, such as adjusting the histogram of the image or changing the tone curve of the image.

[0055] Step S12 is a process performed by the output level adjustment means (M2a) to adjust the output level of the original image data (11A) corresponding to the original image of the visible image (11). In the first embodiment in which the density of the invisible image (12) is constant, step S12 corrects the minimum density of the area in the visible image (11) that is not shared with the invisible image (12) so that it matches the density of the invisible image (12). Next, step S12 will be described in detail.

[0056] Fig. 6(a) is a diagram showing an area (11S) corresponding to the visible image (11) in the base image data (11A) acquired in step S11 superimposed on an area (12S) where the invisible image (12) is formed, and Fig. 6(b) is a diagram explaining an area in the visible image (11) that is not shared with the invisible image (12). As shown in Fig. 6(a), the visible image (11) is also formed in the area (12S) where the invisible image (12) is formed, so the base image data (11A) and the base image data (12A) are image data that share a portion of the same area. On the other hand, the area in the visible image (11) that is not shared with the invisible image (12) refers to the area obtained by excluding the area (12S) where the invisible image (12) is formed from the area (11S) corresponding to the visible image (11), as shown in Fig. 6(b), and in step S12, density correction is performed on the area obtained by excluding the area (12S) where the invisible image (12) is formed from the area (11S) corresponding to the visible image (11). The area obtained by excluding the area (12S) where the invisible image (12) is formed from the area (11S) corresponding to the visible image (11) shown in Fig. 6(b) corresponds to the background of the invisible image (12), and therefore, hereinafter, this area will be described as the "background part (13S) of the visible image."

[0057] In the method for creating data for anti-counterfeit printed matter of the present invention, the data for the visible image (11A) is reproduced by combining an image in which the background portion (13S) of the visible image is density-corrected with data for a density-corrected image (12B) in which the original image data (12A) of the invisible image (12) is output-level corrected. Therefore, in step S12, a process is performed to increase the density of the background portion (13S) of the visible image in advance. As described above, the density of the density-corrected image (12B) corresponding to the invisible image (12) is 20% (gray level 204), and the density of the original image data (11A) corresponding to the visible image (11) ranges from 0% (gray level 255) to 100% (gray level 0). Therefore, as shown in FIG. 7(a), the density of the background portion (13S) of the visible image is corrected from 20% (gray level 204) to 100% (gray level 0), thereby darkening the density of the background portion (13S) of the visible image (FIG. 7(b)). Hereinafter, the image data obtained by density-correcting the background portion (13S) of the visible image (11) from the original image data (11A) corresponding to the visible image (11) in step S12 shown in Fig. 7(a) will be referred to as "corrected visible image data (21A)." Note that the process of density-correcting the background portion (13S) of the visible image from 20% (gray level 204) to 100% (gray level 0) generally corresponds to a process of linearly compressing the density of an image, and density correction is performed for each pixel constituting the background portion (13S) of the visible image using the following formula:

[0058] [Number 1] TIFF2025119213000002.tif32161

[0059] For comparison, Fig. 7(c) is a diagram showing original image data (11A) corresponding to the visible image (11) before density correction in step S12. In the corrected visible image data (21A) shown in Fig. 7(a), the area (12S) overlapping with the density-corrected image (12B) corresponding to the invisible image (12) remains the original image data (11A) of the visible image (11) shown in Fig. 7(c) acquired in step S11, and only the background part (13S) of the visible image is density-corrected to be darker.

[0060] Here, an example has been described in which density correction is performed so that the minimum density value of the background portion (13S) of the visible image becomes 20%, which is the density of the density-corrected image (12B), but in the present invention, density correction is performed so that the minimum density value of the background portion (13S) of the visible image becomes the maximum density value of the original image data (12A) of the invisible image (12) (when step S23 is not performed) or the maximum density value of the density-corrected image (12B). Also, although an example of linear compression has been described for the density correction performed in step 12, the brightness of shadows, intermediate tones, and highlights may be adjusted as appropriate depending on the tone of the printed matter to be produced.

[0061] (pseudo RGB) Next, the color conversion process of the density-corrected visible image correction data (21A) performed by the color conversion means (M2c) in step S13 will be described. FIG. 8 shows a pseudo RGB pattern used in the color conversion process of step S13. As an example, this pseudo RGB pattern consists of nine pixels (3 × 3), each of which has three pseudo red (R), three pseudo green (G), and three pseudo blue (B) pixels. Thus, in the pattern used for color conversion in this embodiment, the number of pseudo red (R), pseudo green (G), and pseudo blue (B) pixels is the same. This results in an overall appearance of gray without bias toward any one color. Note that the arrangement of the pseudo red (R), pseudo green (G), and pseudo blue (B) pixels in the pseudo RGB pattern used in the color conversion of step S13 of the present invention is not limited to that shown in FIG. 8, and it is sufficient that the number of pseudo red (R), pseudo green (G), and pseudo blue (B) pixels in a certain area is the same. For example, the area may be configured to consist of 36 pixels (6x6) (not shown), with equal numbers of pseudo red (R), pseudo green (G), and pseudo blue (B) pixels arranged at regular intervals. Furthermore, the pseudo red (R), pseudo green (G), and pseudo blue (B) pixels do not have to be equal in number or arranged at regular intervals, as long as the overall pseudo RGB pattern is perceived as gray without being biased toward any one color.

[0062] Here, the color data of each pixel is represented by an RGB value (gray level). The pseudo red (R) shown in Figure 8 is an example where the red (R) gray level is 230, the green (G) gray level is 0, and the blue (B) gray level is 19, the pseudo green (G) is an example where the red (R) gray level is 0, the green (G) gray level is 153, and the blue (B) gray level is 69, and the pseudo blue (B) is an example where the red (R) gray level is 30, the green (G) gray level is 33, and the blue (B) gray level is 136.

[0063] When printed out by a printer, if the R, G, and B values of each pixel are equal to or greater than the R, G, and B values of the pseudo red (R), pseudo green (G), and pseudo blue (B) in this pseudo RGB pattern, that is, if they are brighter than the brightness indicated by these values, then they will be printed in cyan (C), magenta (M), and yellow (Y) inks that do not contain infrared-absorbing pigments. Therefore, there is no risk that the background portion (13S) in the visible image will be printed in black (K), which contains infrared-absorbing pigments.

[0064] However, if the R value, G value, and B value of each pixel are lower than the respective RGB values of the pseudo RGB in the pseudo RGB pattern, there is a risk that the background portion (13S) of the visible image will be printed with black (K) ink containing infrared-absorbing pigment, which will hinder the visibility of the visible image (11) and the invisible image (12).

[0065] FIG. 9(a) shows a partial area of the visible image correction data (21A) that is color converted in step S13, and FIG. 9(b) is a diagram showing the color pattern of each pixel (6×6) in an enlarged view of a part of the area shown in FIG. 9(a).

[0066] From the pixel values shown in Figure 9(b), it can be seen that before color conversion, the visible image correction data (21A) includes not only chromatic colors but also achromatic colors in which all RGB values are the same. For each pixel shown in Figure 9(b), if the gray levels of red (R), green (G), and blue (B) are all the same, for example, white is all 255, gray is all 204, 153, 102, or 51, and black is all 0, resulting in an achromatic color. In this way, achromatic colors have the same red (R), green (G), and blue (B) values, while chromatic colors have at least one different red (R), green (G), and blue (B) value.

[0067] When a visible image (11) containing such achromatic colors is printed (excluding white), the printer driver uses black (K), which contains infrared-absorbing pigment, in the background portion (13S) of the visible image, making it impossible to distinguish it from the invisible image (12), resulting in a situation in which the visible image (11) and the invisible image (12) cannot be reproduced as intended. Therefore, the following formula is used to convert the pixels containing achromatic colors into chromatic pixels for the pre-color-conversion visible image correction data (21A) (position coordinates expressed as (x, y)):

[0068] [Number 2] TIFF2025119213000003.tif15160

[0069] where R (x,y) , G (x,y) and B (x,y) are the converted RGB values, R 2(x,y) , G 2(x,y) and B 2(x,y) are the RGB values in the pseudo RGB pattern, R 1(x,y) , G 1(x,y) and B 1(x,y) indicates the RGB values of the image before conversion.

[0070] In this way, when printed out by a printer, the term (R 2(x,y) , G 2(x,y) , B 2(x,y) ) and a term (R 1(x,y) , G 1(x,y) , B 1(x,y) ) is used. Here, as mentioned above, the R of the pseudo RGB pattern is 2(x,y) , G 2(x,y) , B 2(x,y) Each RGB value in corresponds to the lower limit to prevent printing using black (K) ink containing infrared absorbing pigments, and if the value falls below this lower limit, the printer driver may use black (K) ink.

[0071] In the above formula, the R of the pseudo RGB pattern 2(x,y) , G 2(x,y) and B 2(x,y) When only the term is used, the achromatic parts are converted to chromatic colors, and the image as a whole has approximately the same number of pseudo red (R), pseudo green (G), and pseudo blue (B) pixels, so although it is not printed in black (K) ink, it is converted to an achromatic gray as a whole, and the R of the image data before color conversion 1(x,y) , G 1(x,y) and B 1(x,y) Therefore, the color of the image data before color conversion is reflected by the following terms:

[0072] [Number 3] TIFF2025119213000004.tif17101

[0073] Here, the RGB values of the pseudo RGB pattern (R 2(x,y) , G 2(x,y) , B 2(x,y) ) to the RGB value of the image data before conversion (R 1(x,y) , G 1(x,y) , B 1(x,y) ) can be simply added to reflect the color of the image data before correction, but the density value will exceed 255, destroying the color balance. So, for example, if we take pseudo R (red), 2(x,y) To subtract the amount (R2) that was raised by adding (255-R 2(x,y) ) and divide this term by 255, so that the value does not exceed 255 in 256 gradations. 2(x,y) ) / 255) can represent the pseudo R (red) component. That is, ((255-R 2(x,y) ) / 255) is the image data before color conversion, R 1(x,y) By multiplying by , the image data before conversion R is converted while maintaining color balance without exceeding 255. 1(x,y) It is possible to reflect the color of R 2(x,y) and (R 1(x,y) ·(255-R 2(x,y)) / 255), the result is 255. The above explanation has been given using pseudo red (R) as an example, but the same applies to pseudo green (G) and pseudo blue (B), so explanation will be omitted. In the following explanation, the image data obtained by color-converting the visible image correction data (21A) in step S13 will be explained as "color-converted visible image data (31A)."

[0074] Figure 10(a) shows a portion of the image after color conversion in step S13, and Figure 10(b) shows an enlarged view of the color pattern of each pixel (6 x 6). The color pattern of each pixel after color conversion in step S13 shown in Figure 10(b) reflects the color of the visible image (11) before color conversion shown in Figure 9(b), but the gray levels of red (R), green (G), and blue (B) in each pixel all have different values, and all of the achromatic pixels included have been converted to chromatic colors. As a result, when the visible image (11) is printed out, the background area (13S) where the invisible image (12) does not exist is printed using cyan (C), magenta (M), and yellow (Y) inks that do not contain infrared-absorbing pigments, without using black (K) ink containing infrared-absorbing pigments, thereby differentiating it from the invisible image (12). This allows the visible image (11) and the invisible image (12) to be reproduced as intended.

[0075] Furthermore, as shown in Figure 10(b), the gray levels of red (R), green (G), and blue (B) for each pixel vary with gradation from 0% to 100% density, resulting in the inclusion of intermediate tones. As mentioned above, conventionally, when achromatic pixels are included in a visible image, they are replaced with a single color—either cyan (C), magenta (M), or yellow (Y)—at either 0% or 100% density, or with a single color—either a combination of two of these colors—pseudo red (R), pseudo green (G), or pseudo blue (B)—at either 0% or 100% density. As a result, there is no intermediate tone region other than 0% or 100% density, resulting in poor color reproducibility. Therefore, it has been impossible to practically create beautiful images with gradations, such as portraits or landscapes. In contrast to this, according to this embodiment, by performing color conversion using a pseudo RGB pattern as described above, it is possible to avoid the phenomenon in which black (K) ink is used by the printer driver when printing out, and to reproduce halftones as shown in Figure 10(a) while reflecting the color of the image before conversion, and to make achromatic pixels chromatic.

[0076] Next, in step S31, the color-converted visible image data (31A) is combined with a density-corrected image (12B) corresponding to the invisible image (12), and the combined result is output as image data for the anti-counterfeit print (21). During the combination, the RGB values, which are the color data of pixels in the area of the chromatically converted color-converted visible image data (31A) where the density-corrected image (12B) corresponding to the invisible image (12) is combined, are replaced with the density value of the invisible image (12) (in this embodiment, 20% (gray level 204)).

[0077] 11 is a diagram showing the process of combining the color-converted visible image data (31A) with the density-corrected image (12B) corresponding to the invisible image (12) in step S31, and the image data (40) obtained by combining the color-converted visible image data (31A) with the density-corrected image (12B). When the color-converted visible image data (31A) and the density-corrected image (12B) corresponding to the invisible image (12) are combined, black (K) pixels constituting the density-corrected image (12B) corresponding to the invisible image (12) are added to correspond to the increased density of the background portion (13S) where no invisible image is present in step S12. This causes the density of the background portion (13S) of the visible image (11) to match the density of the area to which the invisible image (12) is added, making it difficult to see the area where the invisible image (12) is formed with the naked eye under normal light in the image data (40) and in the anti-counterfeit printed matter (21) output from the image data (40) by a printer.

[0078] As described above, the achromatic parts of the visible image (11) are all converted to chromatic colors while retaining halftones through the color conversion described above. This makes it possible to accurately distinguish the visible image (11) from the invisible image (12) as intended and print it out without relying on a printer, and to obtain good print quality in terms of the clarity of the visible image (11), color reproducibility, etc.

[0079] The RGB values (gray levels) of pseudo red (R), pseudo green (G), and pseudo blue (B) described in this embodiment differ depending on the type of ink used in the printer that produces the anti-counterfeit printed matter (21), but since printing will not be performed using black (K) if the values are configured to be higher than a certain value, they can be confirmed and set in advance. Note that this embodiment describes pseudo RGB patterns implemented in an inkjet printer (PIXUS iP110, manufactured by Canon Inc.) and a color laser printer (PC6010, manufactured by Ricoh Co., Ltd.).

[0080] (If the invisible image is a grayscale image) In the above explanation, we have explained an example in which the invisible image (12) is the letter "A" with a constant density. Next, as a second embodiment, we will explain a method for creating data for anti-counterfeit printed matter in which an invisible image (12) with gradation is formed by partially varying the density.

[0081] (Second embodiment) 12 is a flow diagram of a method for creating data for anti-counterfeit printed matter when forming an invisible image (12) with gradation by partially varying the density. In the process of each part of the method for creating data for anti-counterfeit printed matter and the device for creating data for anti-counterfeit printed matter that executes the method, a part of the process for adjusting the output level of the base image (11A) corresponding to the visible image (11) in step S12 differs, but the other processes are similar and therefore detailed explanations will be omitted. Furthermore, regarding the visible image (11), an example will be described in which the base image data (11A) shown in FIG. 4(a) above is acquired, and the base image data (11A) corresponding to the visible image (11) has the density histogram shown in FIG. 4(c).

[0082] Fig. 13 is a diagram showing the base image (12A) corresponding to the invisible image (12) acquired in step S21, and here, an example will be described in which the base image (12A) in which the density differs between the left and right halves of the letter "A" shown in Fig. 13(a) is acquired in the form of a grayscale image. Also, as shown in the density histogram in Fig. 13(b), the base image (12A) shown in Fig. 13(a) is an example in which the left half of the letter "A" in the base image (12A) has a density of 50% (gray level 127) and the right half of the letter "A" in the base image (12A) has a density of 25% (gray level 191).

[0083] (Density correction of invisible image step S23) In step S23, the density of the invisible image (12) printed in at least a portion of the printing area on the substrate (22) is adjusted. As described above, the maximum density of the invisible image (12) can be set in the range of 20% to 75%. However, since the visible image (11) is overcast with black, an example is described here, in which the maximum density of the density-corrected image (12B) is set to 20% (gray level 204), and the left half of the letter "A" in the original image (12A) is converted to this density, and the right half of the letter "A" in the original image (12A) is converted to an image with a density of 10% (gray level 229), as shown in FIGS. 14(a) and 14(d). For comparison, FIGS. 14(c) and 14(d) show the original image data (12A) and a density histogram before density adjustment. The density-corrected image (12B) whose density has been corrected in step S23 is corrected while maintaining the density balance between the left and right halves of the character "A" in the original image (12A) shown in FIG. 14(c).

[0084] (Density correction of visible image step S12) In the second embodiment, step S12, which adjusts the output level of the original image data (11A) of the visible image (11), performs density correction of the background portion (13S) of the visible image (11) described in the first embodiment (described as "step S12A" in the second embodiment). However, as described in paragraph (0060), this process performs density correction in step S12A by setting 20%, which is the maximum density of the density-corrected image (12B), as the minimum density of the background portion (13S) of the visible image. Specifically, similar to the visible image correction data (21A) and its density histogram shown in Figure 7(a), the density of the background portion (13S) of the visible image is set to 20% (gray level 204), and corrected to 100% density (gray level 0), thereby darkening the density of the background portion (13S) of the visible image. In the second embodiment, if step 23 is not performed, the maximum density value of the original image data (12A) of the invisible image (12) is set as the minimum density value of the background part (13S) of the visible image, and the density correction of step S12A is performed.

[0085] In step S12 of the second embodiment, density correction is also performed on the area in the density-corrected image (12B) of the invisible image (12) where the right half of the character "A" overlaps with the visible image correction data (21A) (step S12B). FIG. 15(a) is a diagram showing the area (14S) where the right half of the character "A" in the invisible image (12) overlaps with the visible image correction data (21A), which is density corrected in step S12B. FIG. 15(b) is a diagram showing the density-corrected image (12B) in which the density of the left half of the character "A" has been corrected to 20% and the density of the right half of the character "A" has been corrected to 10% in step S23.

[0086] In the second embodiment, the reason for correcting the density of the area (14S) where the right half of the letter "A" in the density-corrected image (12B) overlaps with the visible image correction data (21A) is that, as in the first embodiment, when the visible image correction data (21A) in which the background part (13S) of the visible image has been density-corrected from 20% density (gray level 204) to 100% density (gray level 0) is combined with the left half of the letter "A" in the density-corrected image (12B) that has been density-corrected to 20%, the original image data (11A) of the visible image (11) is reproduced, but when the right half of the letter "A" in the density-corrected image (12B) that has been density-corrected to 10% density is combined, the density becomes too low and the original image data (11A) of the visible image (11) is not reproduced. 15(c) and 15(d), the density of the area (14S) where the right half of the character "A" in the density-corrected image (12B) overlaps with the visible image correction data (21A) is corrected from 10% (gray level 229) to 100% (gray level 0), thereby correcting the density so that the right half of the character "A" in the density-corrected image (12B) becomes darker. The density correction in step S12B is performed using the following formula:

[0087] [Number 4] TIFF2025119213000005.tif38160

[0088] In the second embodiment, the process of performing color conversion on the visible image correction data (21A) in step S13 and the process of combining the color-converted visible image data (31A) with the density-corrected image (12B) corresponding to the invisible image (12) in step S31 are the same as those in the first embodiment, and therefore detailed descriptions thereof will be omitted. Fig. 16 is a diagram schematically illustrating the process of combining the color-converted visible image data (31A) with the density-corrected image (12B) corresponding to the invisible image (12) in step S31, and image data (40) obtained by combining the color-converted visible image data (31A) with the density-corrected image (12B). As shown in FIG. 16, in the process of step S31 in which the color-converted visible image data (31A) is combined with the density-corrected image (12B) corresponding to the invisible image (12), black (K) pixels that constitute the density-corrected image (12B) corresponding to the invisible image (12) are added in step S12 to correspond to the increased density of the background area (13S) where no invisible image exists and the area (14S) overlapping with the right half of the character "A." This makes it difficult to see the area where the invisible image (12) is formed with the naked eye under normal light in the image data (40) and the anti-counterfeit printed matter (21) output from the image data (40) by a printer.

[0089] In the second embodiment, the invisible image (12) has been described as an example in which the left and right halves of the letter "A" shown in Fig. 13 have different densities, but the invisible image (12) may be an image composed of three or more different densities. In this case, density correction in step S12B is performed for each pixel of the original image data (11A) of the visible image (11) that overlaps at the same position, corresponding to each pixel that composes the density-corrected image (12B).

[0090] 17 shows an example of a density-corrected image (12B) obtained by performing density correction in step S23 on image data (12A) of the letter "A" in which the density gradually changes from top to bottom, where the uppermost pixel (12b1) has a density of 10% (gray level 229), the lowermost pixel (12b3) has a density of 20% (gray level 204), and the pixel (12b2) therebetween has a density of 15% (gray level 217). Since the density correction in step S12B is not performed on the original image data (11A) that overlaps with the pixel (12b3) with the highest density in the density-corrected image (12B), an example of performing density correction on the original image data (11A) of the visible image (11) corresponding to the two pixels (12b1, 12b2) shown in FIG.

[0091] Fig. 18(a) is a diagram showing pixels (11a1, 11a2) of the original image data (11A) corresponding to the visible image (11) that overlap with two pixels (12b1, 12b2) that make up the density-corrected image (12B), Fig. 18(b) is a density histogram of the pixel (11a1), and Fig. 18(c) is a density histogram of the pixel (11a2). Here, an example will be described in which the pixel (11a1) has a density of 50% (gray level 127) and the pixel (11a2) has a density of 30% (gray level 178).

[0092] 19(a) shows a density histogram of pixel (11a1) after density correction in step S12B. The 50% density (gray level 127) of pixel (11a1) before density correction is corrected to a density of 100% (gray level 0), with the 10% density (gray level 229) of pixel (12b1) in density-corrected image (12B) as the minimum value, converting the pixel into a pixel darker than pixel (11a1) before correction. The process of correcting pixel (11a1) from 10% density (gray level 229) to 100% density (gray level 0) corresponds to a process of compressing the density of pixel (11a1), and the 50% density (gray level 127) of pixel (11a1) before density correction is corrected to a density of 55% (gray level 105).

[0093] 19(b) shows a density histogram of pixel (11a2) after density correction in step S12B. The 30% density (gray level 178) of pixel (11a2) before density correction is corrected to a density of 100% (gray level 0), with the 15% density (gray level 217) of pixel (12b2) in density-corrected image (12B) as the minimum value, converting the pixel into a pixel darker than pixel (11a2) before correction. The process of correcting pixel (11a2) from 15% density (gray level 217) to 100% density (gray level 0) corresponds to a process of compressing the density of pixel (11a2), and the 30% density (gray level 178) of pixel (11a2) before density correction is corrected to a density of 41% (gray level 150).

[0094] As described above, in the case of a density-corrected image (12B) having partially different densities as shown in Fig. 17, the process of step S12B is performed on each pixel in the area where the density-corrected image (12B) and the original image data (11A) overlap (excluding pixels with a density of 20%, which is the maximum value of the density of the density-corrected image (12B)), thereby obtaining corrected visible image data (21A) shown in Fig. 20. As a result of the density correction performed in step S12B, the area (14S) where the density-corrected image (12B) overlaps in the corrected visible image data (21A) shown in Fig. 20 becomes an image in which the density of the character "A" in the invisible image (12B) is reflected (the density gradually changes from top to bottom). In the visible image correction data (21A) shown in FIG. 20, the background portion (13S) of the visible image is density-corrected so that the density of the background portion (13S) of the visible image becomes darker by correcting the density of the background portion (13S) of the visible image from 20% (gray level 204), which is the maximum density of the density-corrected image (12B), to 100% (gray level 0), in the same manner as in the process described in the first embodiment.

[0095] The process of color conversion of the visible image correction data (21A) in step S13 of the second embodiment is the same as in the first embodiment, so a description thereof will be omitted. Next, step S31 of the second embodiment will be described.

[0096] 21 is a diagram schematically illustrating the process of combining the color-converted visible image data (31A) with the density-corrected image (12B) corresponding to the invisible image (12) in step S31 of the second embodiment, and the image data (40) obtained by combining the color-converted visible image data (31A) with the density-corrected image (12B). By adding black (K) pixels that constitute the color-converted visible image data (31A) and the density-corrected image (12B) corresponding to the invisible image (12) shown in FIG. 21, it is possible to make it difficult to see the area where the invisible image (12) is formed with the naked eye under normal light in the image data (40) and in the anti-counterfeit printed matter (21) output from the image data (40) by a printer.

[0097] (Data creation software) Software for creating data for anti-counterfeit printed matter according to one embodiment of the present invention is software that causes a computer to execute the data creation method according to the above embodiment, thereby making it possible to create data for anti-counterfeit printed matter. According to the method and software for creating data for anti-counterfeit printed matter of the present embodiment described above, it is possible to obtain good print quality in terms of the concealment of invisible images when observed with the naked eye under normal light, the visibility of invisible images when observed under infrared light irradiation, and the clarity of visible images, without relying on a printer.In particular, it is possible to improve the color reproducibility including half-tones of visible images, and it is possible to provide a method and software for creating data for anti-counterfeit printed matter that can be used to practically produce beautiful images with gradations such as portraits and landscape paintings.

[0098] Although the embodiments of the present invention have been described, these embodiments are presented as examples and are not intended to limit the technical scope of the invention. This novel embodiment can be embodied in various other forms, and various omissions, substitutions, and modifications can be made without departing from the spirit of the invention. These embodiments and their modifications are included within the technical scope and spirit of the invention, and are also included in the inventions and their equivalents set forth in the claims. [Explanation of symbols]

[0099] 11 Visible images 12 Invisible Images 21w anti-counterfeiting printed matter 22 Base material 11A Basic image data (visible image) 12A Basic image data (invisible image) 12B Density correction image (invisible image) 21A Visible Image Correction Data 31A Color conversion visible image data 40 Image data M1 Input Method M1a Visible image input means M1b Invisible image input means M2 editing method M2a output level adjustment means M2b CMYK image to grayscale image conversion tool M2c color conversion method M2d synthesis means M3 display means M4 Output Method M5 communication interface M6 Database M7 Storage means

Claims

1. A method for creating data for an anti-counterfeit printed matter, comprising the steps of: providing a visible image formed with ink that does not contain an infrared absorbing dye and an invisible image formed with ink that contains an infrared absorbing dye in at least a portion of a printing area of a substrate; and the visible image and the invisible image sharing a portion of the same area, The creation method includes a step of acquiring first image data corresponding to an original image of the visible image and second image data corresponding to an original image of the invisible image; generating density-corrected image data of the visible image by correcting the density of the first image data so that the minimum density value of an area not shared with the invisible image becomes the maximum density value of the second image data; generating color-converted image data of the visible image by a process of converting the density-corrected image data of the visible image into a chromatic color that is not converted into black (K), and a color conversion process that reflects the color of the first image data; A method for creating data for anti-counterfeit printed matter, comprising a step of combining the color-converted image data of the visible image with the second image data.

2. A method for creating data for anti-counterfeit printed matter as described in claim 1, characterized in that when the invisible image is a gradation image with partially different densities, the step of generating the density-corrected image data corrects the density of each pixel of the first image data in an area shared with the invisible image from the density of the pixel of the second image data corresponding to each pixel of the first image data to a range of 100% density.

3. In the color conversion processing step, a pseudo RGB pattern consisting of pseudo red (R), pseudo green (G), and pseudo blue (B) having predetermined red (R), green (G), and blue (B) values that are not converted to black (K) is used for each pixel constituting the density-corrected image data, When the position of each pixel constituting the density-corrected image data is expressed as (x, y), the red (R １（ｘ，ｙ） ), Green (G １（ｘ，ｙ） ) and Blue (B １（ｘ，ｙ） ) and the pseudo red (R ２（ｘ，ｙ） ), pseudo green (G ２（ｘ，ｙ） ) and pseudo blue (B ２（ｘ，ｙ） ) and the pseudo red (R （ｘ，ｙ） ), pseudo green (G （ｘ，ｙ） ) and pseudo blue (B （ｘ，ｙ） 3. The method for creating data for anti-counterfeit printed matter according to claim 1, wherein the following relationship is satisfied between the data and the first and second data: Formula (I) R （ｘ，ｙ） =R ２（ｘ，ｙ） +R １（ｘ，ｙ） ・(255-R ２（ｘ，ｙ） ) / 255; Formula (II)G （ｘ，ｙ） = G ２（ｘ，ｙ） +G １（ｘ，ｙ） ・(255-G ２（ｘ，ｙ） ) / 255; Formula (III)B （ｘ，ｙ） =B ２（ｘ，ｙ） +B １（ｘ，ｙ） ・(255-B ２（ｘ，ｙ） ) / 255;

4. 3. Software for creating data for anti-counterfeit printed matter, the software causing a computer to execute the method for creating data for anti-counterfeit printed matter according to claim 1 or 2.

5. 4. Software for creating data for anti-counterfeit printed matter, the software causing a computer to execute the method for creating data for anti-counterfeit printed matter according to claim 3.

Images