JP2016024776A - Two-dimensional code image generation method and two-dimensional code image - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a two-dimensional code image generation method and a two-dimensional code image allowing two-dimensional code data to be buried in a normal design image without the feeling of discomfort.SOLUTION: Each black-and-white module 11 forming a QR code (registered trademark) 10 is reduced, a margin area 16 in which reduction modules 15 are not displayed is formed around each reduction module 15, and the QR code 10 is formed by the reduction modules 15. Superimposed normal images are defined as an aggregate of fine point areas 18, a white or black fixed luminance value is given for each point area 18 of the images, error diffusion processing is performed for each point area 18, and the fixed luminance value of the point area 18 is determined. The normal image formed by the aggregate of the point areas 18 set to the fixed luminance value is superimposed on the margin area 16 of a display area by the reduction modules 15. In an arrangement position of the reduction modules 15, the fixed luminance value of the point areas 18 at the position is defined as a fixed luminance value of the reduction modules 15, and a difference in the luminance value with the normal image at the position is error-diffusion processed and is defined as a fixed luminance value of the surrounding point areas 18.SELECTED DRAWING: Figure 2

Description

  The present invention relates to a two-dimensional code image generation method and a two-dimensional code image for forming and displaying an image in which a two-dimensional code is embedded in various visually recognizable images.

  In recent years, two-dimensional codes such as QR codes (registered trademark, JIS X 0510, hereinafter simply referred to as QR codes) have been displayed on the appearance of various advertising media. In this QR code, a series of squares of the same size of black and white, which are a dark module and a light module, are displayed at predetermined positions, and the displayed two-dimensional code is visually visible as random light and dark. is there. Therefore, even if a part or all of the QR code is combined with a pattern such as a specific logo, character string, figure, or picture, it cannot be displayed as it is.

  Therefore, as disclosed in Patent Document 1, by using the padding bit pattern of the QR code, a part or all of the two-dimensional code is not a monochrome dot but a specific logo or character string pattern. It has been proposed to form as This QR code pattern forms a two-dimensional code by setting a large range of padding bits excluding information bits, and adds end information of information bits to information to be encoded. , Redundant information bits are added.

  Furthermore, as disclosed in Patent Documents 2 and 3, a method of generating a QR code in which an image that can be visually recognized is embedded in a two-dimensional code has also been proposed. In this two-dimensional code generation method, the original data to be read from the two-dimensional code and the unused data area of the two-dimensional code corresponding to the data amount of the original data are specified, and the binarized design corresponding to the unused data area The data is converted into a bit code obtained by inverse conversion based on the format information of the two-dimensional code, the bit code and the bit code of the original data are converted based on the format information of the two-dimensional code, and the two-dimensional code is converted. Is to be generated. According to this two-dimensional code generation method, data for generating a two-dimensional code includes information on the original data, and the original data is displayed on the two-dimensional code while displaying the design pattern on the two-dimensional code. Can be read.

  In addition, as disclosed in Patent Documents 4 and 5, there is also an image processing method for generating embedded image information by embedding data as additional information in a visually invisible predetermined state in an invisible state. there were. In this image processing method, the additional information to be embedded is processed using an error diffusion method or the like so that the presence of the additional information is not visually recognized.

  In addition, as disclosed in Non-Patent Document 1, a method of superimposing a binarized design image of a normal image desired to be superimposed on a QR code by using an error diffusion method as a QR code module is reduced. It has been proposed by the present inventor. This non-patent document 1 does not show how error diffusion is performed in consideration of the reduced module.

JP 2009-163720 A Japanese Patent No. 3953501 Japanese Patent No. 3957735 Japanese Patent Laid-Open No. 11-168616 JP 2007-124502 A

2013 IEICE General Conference Information and Systems Proceedings 2 P170 Creation of QR code to improve appearance by superimposing error diffusion images

  However, the two-dimensional code generation method disclosed in Patent Document 1 displays an illustration of an arbitrary dot pattern using the padding bits of the QR code, and the bit pattern portion of the two-dimensional code and the illustration The image part is separated and written together. Therefore, the appearance of the QR code is not recognizable as a design other than the bit pattern, and both the area of the two-dimensional code and the area of the illustration image are narrow, and the amount of information is small, so that it can be displayed as a display image. Is not good.

  Furthermore, the two-dimensional code generation method disclosed in Patent Documents 2 and 3 also uses a non-use data area of a two-dimensional code and superimposes a normal design image on the non-use data area. The code display is directly present in the design image. Accordingly, the design image can be visually recognized in the two-dimensional code, but the image in the two-dimensional code display area becomes unnatural as a whole, and the design image is displayed in the two-dimensional code. The effect diminished.

  In addition, in the case of the image processing methods disclosed in Patent Documents 4 and 5, additional information such as code information is superimposed in an unrecognizable manner in the design image. It cannot be recognized without using a dedicated decoding means. Moreover, since it cannot be visually confirmed that the additional information is present in the image information, it can be used only by a person who knows that the additional information is present in the image, and the information is actively read like a QR code. It cannot be used for advertisement images intended to be received.

  The present invention has been made in view of the above-described background art, and includes a two-dimensional code image generation method and a two-dimensional code image capable of superimposing two-dimensional code data on a normal design image so as to be visually observable. The purpose is to provide.

  The present invention provides a two-dimensional code image generation method for superimposing a normal image, which is an image that can be viewed with an arbitrary design, into a two-dimensional code image displayed in black and white, and the black and white constituting the two-dimensional code. Each module is reduced to a reduction module, the two-dimensional code is formed by the reduction module, a blank area where the reduction module is not displayed is formed around each of the reduction modules, and the normal image is defined as a predetermined module. Display of the two-dimensional code on which the normal image is superimposed by giving a fixed luminance value of at least white or black for each point area of the display area of the two-dimensional code, as a collection of point areas with minute brightness An image of a region is formed, and at that time, an error diffusion process is performed for each point region to determine the fixed luminance value of the point region, and the reduction mode In the margin area of the display area of the two-dimensional code by the rule, the normal image composed of the set of the point areas set to the fixed luminance value is overlaid, and the reduction of the display area of the two-dimensional code is performed. At the module arrangement position, when setting the fixed luminance value of the point area at that position, the luminance value of the reduction module is determined as the fixed luminance value of the point area regardless of the luminance value of the normal image, The difference between the determined fixed luminance value and the error-diffused luminance value at that position is diffused to the surrounding point region as the next error, and the fixed luminance value of the point region is A two-dimensional code image generation method for determining and forming a two-dimensional code image in which the image of the two-dimensional code is superimposed on the normal image.

  The difference in size between the point area and the reduction module is formed within 20% of each other. In particular, the size of the point area and the size of the reduction module is preferably the same.

  Further, the error diffusion process may be such that a point having a black and white binary value and a gray fixed luminance value in between is formed by the point area, and the two-dimensional code is superimposed on the normal image.

  The two-dimensional code is a QR code, and the reduction module is set to an area ratio of 20% or less of the module before reduction and 5% or more.

  The present invention also provides a two-dimensional code image in which a normal image, which is a normal design image, is superimposed on a two-dimensional code displayed in black and white binary, and each black and white module constituting the two-dimensional code is provided. The two-dimensional code is formed by the reduction module by reducing the reduced module, a blank area where the reduced module is not displayed is formed around each of the reduced modules, and the normal image is changed to a minute dot with a predetermined luminance. An image of the display region of the two-dimensional code on which the normal image is superimposed by giving a fixed luminance value of at least white or black for each point region of the display region of the two-dimensional code, as a collection of regions. Forming a fixed luminance value for each of the point regions, determining the fixed luminance value of the point region, and displaying the two-dimensional code display region by the reduction module. In the margin area, the normal image composed of the collection of the point areas set to the fixed luminance value is overlaid, and the arrangement position of the reduction module in the display area of the two-dimensional code is the position at the position. When setting the fixed luminance value of the point area, the luminance value of the reduction module is determined as the fixed luminance value of the point area regardless of the luminance value of the normal image, and the determined fixed luminance value and the position at the position are determined. The error diffusion process for diffusing the difference from the error-diffused luminance value as the next error to the surrounding point area is performed, the fixed luminance value of the point area is determined, and the two-dimensional code of the normal image is determined. It is a two-dimensional code image formed by superimposing images.

  According to the two-dimensional code image generation method and the two-dimensional code image of the present invention, a normal design image that can be visually recognized by a person is superimposed on an image that has been subjected to a two-dimensional code that can be visually recognized by a person. It is possible to display a normal image that is not a design image, and to reliably and easily read and decode a two-dimensional code provided in the image by a reading device. As a result, it is possible to use the area to which the two-dimensional code has been applied in an appearance state close to that of a normal design image, so that the range of use of the two-dimensional code image can be expanded, and the user of the two-dimensional code is also good. Visual information and accurate code information can be obtained.

It is a figure explaining the QR code which is a two-dimensional code used for one Embodiment of the two-dimensional code image generation method of this invention. It is a figure which shows the two-dimensional code by the reduction module of this embodiment. It is a schematic diagram explaining the error diffusion process used for the two-dimensional code image generation method of this embodiment. It is a schematic diagram explaining in one dimension a specific example of error diffusion processing used in the two-dimensional code image generation method of this embodiment. It is a schematic diagram explaining in one dimension a specific example of performing error diffusion processing by adding a reduction module in the error diffusion processing used in the two-dimensional code image generation method of this embodiment. It is explanatory drawing which shows the ratio of the brightness | luminance diffused in the periphery in the other example of the error diffusion process used for the two-dimensional code image generation method of this embodiment. It is a schematic diagram explaining the other example of the error diffusion process used for the two-dimensional code image generation method of this embodiment. It is a schematic diagram explaining the other example of the error diffusion process used for the two-dimensional code image generation method of this embodiment. It is a figure which shows the example (a), (b) of the two-dimensional code image formed with the two-dimensional code image generation method of this embodiment. It is a figure which shows the design image (a) superimposed on QR Code by the two-dimensional code image generation method of this embodiment, and the design image (b) which carried out error diffusion by the Freud Steinberg method. It is a schematic diagram explaining the further another example of the error diffusion process used for the two-dimensional code image generation method of this embodiment. It is a figure which shows each Example (a), (b), (c), (d) of the reduction module of QR Code by the two-dimensional code image generation method of this invention. In the embodiment of the two-dimensional code image generation method of the present invention, examples (a), (b), (c), (d), (d) of two-dimensional code images resulting from the superposition of the QR code of the reduction module and the error diffusion image It is a figure which shows e) and (f). It is a figure which shows the example of the quaternary error diffusion QR code image of the two-dimensional code image generation method of this invention.

  Hereinafter, an embodiment of a two-dimensional code image generation method of the present invention will be described with reference to the drawings. The image processing method of this embodiment uses a QR code as a two-dimensional code. Here, the QR code will be briefly described. As shown in FIG. 1, the QR code 10 is drawn as a set of small black and white binary squares, each small square is called a module, and is basically drawn in either black and white. The module 11 of the QR code 10 shown in FIG. 1 is classified into two types of areas called a function pattern area 12 and an encoding area 14.

  The function pattern area 12 sets the coordinates of the QR code 10, modifies the coordinates of the image read by a reading device such as a camera, and the modules in the coding area 14 from the recognized coordinates of the QR code 10. The code information in the coding area 14 can be decoded by correcting the position of 11 and recognizing the code.

  The encoding area 14 is an area in which information recorded in the QR code 10, information used for decoding, and the like are recorded after being encoded by binary numbers composed of black and white binary images. By recognizing the difference in brightness between the modules 11 within 14, the recorded information can be decoded. In the QR code 10, information by the module 11 is represented by a binary number, and the binary number 1 is represented by a black module 11a and 0 is represented by a white module 11b. Further, the encoding area 14 is classified into four types of areas of data code, error correction code, format information, and model number information. The data code records information recorded in the QR code 10, a character mode indicating the information format, the number of characters, and the like. The recording format is determined by the standard, and details thereof are omitted.

  Also, reading and decoding of the QR code 10 are performed by processing based on a predetermined standard, and description thereof is omitted here.

  Next, in the two-dimensional code image generation method according to the embodiment of the present invention, the embedding of the QR code 10 into a design image that is a normal image will be described. First, in the image processing of this embodiment, the QR code 10 module 11 to be embedded in an arbitrary design image, which is a normal image, is reduced at a certain rate as shown in FIG. Superimpose. As shown in FIG. 2, the reduction module 15 has a length of one side of the original white or black module 11 of 1/3 to 1/5 and an area ratio of each module 11 of about 11% to about 11%. Reduced to 4%. By making each original module 11 a white or black reduction module 15, an empty space is made a blank area 16 that can be used freely.

  The normal image to be superimposed on the QR code 10 is binarized into black and white and superimposed. At this time, in order to improve the appearance of the design image that is the superimposed normal image and minimize the sense of incongruity when viewed by humans, the appearance close to the gradation of the original design image using the error diffusion method Image processing is performed so as to obtain a state image.

  An example of image processing by the error diffusion method will be described below. The error diffusion method expresses an image as a collection of fine points in order to represent the visual appearance of a black and white binarized image closer to the original image, and the dark portion of the original image Represents dense gradation of black spots and expresses gradation by reducing the density of black spots in light-colored parts, and expresses an image by performing the following processing. Each of the fine points of the smallest unit by the error diffusion method used here is a point for forming an image to be displayed, and is referred to as a point region 18 in the present invention. The dot area 18 is composed of a plurality of pixels equal to or equal to one pixel as a minimum unit for forming an image. By setting one pixel to one point region 18, the number of processing steps increases, but the finest processing can be performed.

  The concept of the error diffusion method is that, for example, when a 2 × 2 pixel black module 11a as shown in FIG. 3B is drawn in a 4 × 4 pixel region as shown in FIG. A part of the brightness value is diffused around as shown in FIG. In other words, the error diffusion method is an image processing method that adjusts the luminance of an image by diffusing the luminance value so that the average luminance does not change in the entire 4 × 4 pixels in this example. By diffusing the difference in brightness in this way, the average brightness is the same between the image shown in FIG. 3A and the image shown in FIG. It can be made without a great sense of incongruity.

  Next, a specific processing method of the error diffusion method for determining the luminance value of the black and white dot region 18 will be described based on FIG. 4 by taking a one-dimensional case as an example. In this processing, when the point area 18 of the image to be displayed is represented by a luminance value of 256 gradations, the difference when the luminance value of the point area 18 is determined to be white or black is set to the adjacent point area 18. It carries out the carry-over process. Specifically, the threshold value of the luminance value is set to 128, and the difference is carried over to the adjacent point region 18 from the first point region 18 determined as black having a luminance value of 0 or white having a luminance value of 255. In the adjacent point region 18, if the accumulated value that is the sum of the carry-over value and the original luminance value is equal to or greater than the threshold luminance value 128, the fixed luminance value is white, that is, the luminance value 255, and the accumulated luminance value is the threshold value 128. If the value is less than black, the fixed luminance value is black, that is, the luminance value is zero. As described above, the accumulated value is sequentially carried over to the adjacent point regions 18 and the luminance value of the point region 18 is set to a fixed luminance value of white (luminance value 255) or black (luminance value 0).

  First, it is assumed that the luminance value of the original image is the numerical value shown in FIG. In order to display the image of each point area 18 in black and white, in this error diffusion method, the luminance value 65 of the left end point area 18 is less than the threshold value 128 as shown in FIG. The luminance value is set to a fixed luminance value of 0, and the original luminance value 65 is carried over to the adjacent point area 18. In the adjacent point region 18, the luminance value carried over is added to the luminance value 70 of the original image to be 135. Then, as shown in FIG. 4 (2), since the luminance value of the adjacent point region 18 is equal to or greater than the threshold value 128, the luminance value of the point region is set to a fixed luminance value of 255, and the difference from the original luminance value − 120 is further carried over to the adjacent point area 18. Since the original luminance value of the next point area 18 is 136, when the carried luminance value −120 is added, the point area 18 becomes the luminance value 16. Since this luminance value 16 is less than the threshold value 128, as shown in FIG. 4 (3), the luminance value is set to 0 as the fixed luminance value, and the difference luminance value 16 is carried over to the next side. The luminance value of the point area 18 where the luminance value 16 is carried over is added to the original luminance value 140, and the point area 18 becomes a luminance value 156. As a result, the luminance value of the dot region 18 becomes a fixed luminance value of 255, and the difference luminance value −99 is carried forward. By repeating this process, as shown in FIG. 4D, the difference from the original luminance value of the carried-over point area 18 becomes −9, and the fixed luminance value of this point area 18 becomes zero. Similarly, the luminance value is carried over to the adjacent point area 18 by error diffusion, and an image having a fixed luminance value shown in FIG. 4 (4) is formed. In this manner, the original normal image is replaced with a fixed luminance value having a luminance value of 0 or 255 for each point region 18, that is, an image based on a set of black or white point regions 18 by image processing using the error diffusion method.

  Furthermore, according to the present invention, when an image is formed by the error diffusion method, an error diffusion process is performed on the design image, which is the original normal image, in consideration of the brightness value of the QR code image formed by the reduction module 11a. In this process, the brightness value of the original design image and the brightness value of each point area of the QR code formed by the reduction module 15 are taken into consideration, and the reduction module 11a is fixed in the point area 18 where the QR code reduction module 11a is located. The brightness value is set as the fixed brightness value of the point area 18, and the difference from the error-diffused brightness value at that position is diffused around as the error of the adjacent point area. In this way, the error diffusion process is carried forward for the luminance values of the respective point regions 18, and the respective point regions 18 are sequentially set to fixed white or black luminance values. The error diffusion method in this embodiment will be described below based on the specific example of FIG.

  Here, the luminance value of the original normal image is the numerical value shown in FIG. 5A for each point area 18, and the luminance value of the image by the reduction module 15 of the QR code 10 is the numerical value shown in FIG. 5B. Suppose that A space area 16 is provided between the reduction modules 15.

  First, when the superimposed image of the normal image and the QR code 10 is displayed in each point area 18 having a fixed luminance value of white or black, in this error diffusion method, as shown in FIG. Although the luminance value 65 of 18 is less than the threshold value 128, the luminance value of the reduction module 15 at the corresponding position of the QR code 10 superimposed on this point region 18 is a fixed luminance value of 255. Regardless of the luminance value shown in FIG. 5A, the fixed luminance value 255 is white. Then, a luminance value of −190, which is a difference from the original luminance value 65, is carried over to the adjacent point area 18.

  In the adjacent point region 18, the luminance value −190 carried over is added to the luminance value 70 of the original image which is a normal image, and becomes a luminance value −120. As a result, as shown in FIG. 5 (2), the luminance value of the adjacent point region 18 is less than the threshold value 128, so that the luminance value of the point region 18 is set to a fixed luminance value 0, and the difference from the original luminance value. Carry -120 further to the adjacent point area 18. Since the original luminance value of the next point area 18 is 136, when the carried luminance value −120 is added, the point area 18 becomes the luminance value 16. Since this luminance value 16 is less than the threshold value 128, as shown in FIG. 5 (3), the luminance value of the point area 18 is set to a fixed luminance value 0, and the difference luminance value 16 is carried over to the next. In the adjacent point area 18, the luminance value 16 carried over is added to the original luminance value 140, and the point area 18 becomes a luminance value 156.

  In the point area 18 where the luminance value 156 is obtained, the luminance value 0 of the reduction module 15 exists as a fixed luminance value at the corresponding position of the superimposed QR code 10, as shown in FIG. 5B. As shown in FIG. 5 (4), the luminance value of the point area 18 is equal to the fixed luminance value 0 of the QR code 10 corresponding to the point area 18, regardless of the luminance value of the original image and the luminance value carried over. To do. Then, the difference between the determined fixed luminance value 0 and the original luminance value 156 is carried over to the adjacent point area 18 and error diffusion is performed.

  Further, in the adjacent point region 18, the carry-over luminance value 156 is added to become a luminance value 246, and as shown in FIG. 5 (5), this point region 18 becomes white with a fixed luminance value 255, and the difference Bring luminance value -9 to the next. Similarly, the point area 18 in which the luminance value −9 is carried over changes from the original luminance value 234 to the luminance value 225 and is equal to or greater than the threshold value 128. Therefore, as shown in FIG. It becomes white, and the difference luminance value −30 is further carried over to the adjacent point region 18.

  Then, as shown in FIG. 5 (6), the luminance value 98 changes to the luminance value 68 in the point area 18 where the luminance value −30 is carried over. However, as shown in FIG. 5B, the luminance value 255 of the reduction module 15 exists as a fixed luminance value at the corresponding position of the QR code 10 superimposed on the point region 18, and therefore the point region 18 As shown in FIG. 5 (7), the luminance value of the QR code 10 corresponding to the point area 18 is fixed as the fixed luminance value 255 regardless of the luminance value of the original image and the luminance value carried over. White. By setting the point area 18 to the luminance value 255, the luminance value -187 of the difference from the original luminance value 68 is carried over to the adjacent point area 18, and the same processing is performed in the point area 18 at the carried over position. Determine a fixed luminance value.

  This process is sequentially performed for the luminance value of the point area 18 to form an image of the point area 18 shown in FIG. 5 (7), and an image obtained by superimposing the original normal image and the reduction module 15 of the QR code 10 has a luminance value. The image is replaced with an image having a fixed luminance value of 0 or 255, that is, a set of black or white dot regions 18.

  In this way, by forming the two-dimensional code image by applying the error diffusion method based on the luminance value of the design image that is the normal image to be superimposed and the black and white luminance value image of the QR code 10 by the reduction module 15. Even if the QR code 10 is superimposed, an image closer to the original design image can be formed.

  At this time, it is preferable that the difference between the size of one reduction module 15 and the size of one dot region 18 of a design image to be displayed or printed is within 20%, and more preferably by making the difference smooth. An image without a sense of incongruity can be formed.

  As a more specific example of the error diffusion method of the two-dimensional code image generation method of the present invention, there is one based on the Freud Steinberg method shown in FIGS. In this error diffusion method, with respect to the luminance value of the base image, the luminance value of the point area 18 to be processed is determined to be 0 or 255 depending on whether the luminance value is 128 or more as described above, The difference is distributed and accumulated in the point areas 18 adjacent to the four lower right positions of the point area 18 in the ratio shown in FIG.

  For example, as shown in FIG. 7A, when the luminance value of the central point region 18 shown in FIG. 7 is set to white or black and the difference is diffused, the central point region 18 has the luminance value 159. Reference numeral 18 denotes a luminance value 255, and the difference −96 is distributed to four adjacent dot regions as shown in FIG. 7B. The distribution is performed at the ratio shown in FIG. 6, and the value obtained by dividing the difference value (−96) by 16 is multiplied by the number of numerators shown in FIG. 6 and added to the luminance value of the adjacent pixel. Then, the luminance value as shown in FIG.

  Similarly, for example, as shown in FIG. 8A, when the luminance value of the point region 18 to be processed is 80, the point region 18 is black with a luminance value of 0, and the difference luminance value 80 is set to four adjacent luminance values. Distribute to the point area 18 as described above. As a result, the luminance value as shown in FIG. This distribution and accumulation is sequentially performed in each point area 18 to determine the luminance value of each point area 18, that is, whether it is white or black, and a necessary image area is configured by an aggregate of white or black point areas 18. Form.

  An example of a two-dimensional code image formed by the two-dimensional code image generation method of this embodiment is shown in FIGS. FIG. 10A shows a design image which is a normal image superimposed on the QR code 10, and FIG. 10B shows an image obtained by binarizing the design image and error-diffusing by the Freud Steinberg method.

  As a result, as shown in FIG. 9A, compared with a two-dimensional code image obtained by simply superimposing a QR code on an error-diffused design image, an error diffusion as shown in FIG. At this time, the luminance value of the reduction area 15 is taken into consideration for the luminance value of the point area 18 at the position, and the luminance value of the point area 18 including the difference from the luminance value of the reduction module 15 is subjected to error diffusion processing to obtain a binary value. As a result, it is possible to form a two-dimensional code image that is more comfortable.

  According to the two-dimensional code image generation method of this embodiment, a normal design image that can be visually recognized by a person is superimposed on an image that displays a two-dimensional code that can be visually recognized by a human. It enables the formation of some normal images. As a result, it is possible to use the area to which the two-dimensional code has been applied as a normal design image, and the range of use of the two-dimensional code image can be widened. Accurate code information can be obtained.

  Note that the error diffusion method of the present invention is not limited to the above-described embodiment. In addition to forming an error diffusion image in a black and white binary point area, as schematically shown in FIG. May be divided into four stages for error diffusion. In this case, for example, as shown in FIG. 11A, the luminance values of the threshold values of the boundaries are 63, 128, and 192. In FIG. 11 (a), the luminance is changed from black to white step by step for convenience. Then, as shown in FIG. 11B, a luminance value of 63 or less is set to black with a fixed luminance value of 0, a luminance value of 64 to 127 is set to a fixed luminance value of 128, a dark gray dot region, and a luminance value of 128 to 191 is fixed. The brightness value 192 is represented by a light gray dot region. Further, a luminance value of 192 or more is set as a white dot region as a fixed luminance value 255. Other processes are the same as those described above.

  As a result, smoother gradation expression can be achieved, and a QR code superimposed image with a more uncomfortable feeling can be formed.

  Next, an example of a two-dimensional code image created by the two-dimensional code image generation method of the present invention will be described below. In this embodiment, QR code error correction level H type (about 30%), size 6 (cm), still image resolution 2560 × 2048 (pixel), moving image resolution 1920 × 1080 (pixel), and reading software QRdeCODE are used. It was.

  First, the QR code module was scaled down to verify how large it can be read. When the area of the original module that has not been reduced is 100%, the ratio of the size of the reduced module is shown in Table 1 as the module reduction rate. Furthermore, the QR code of the reduction module created in this experiment is shown in FIGS. 12 (a), (b), (c), and (d).

The result of reading the QR code of the reduction module according to this embodiment is shown in the determination of Table 1. The determination result ○ indicates that reading is performed within 5 seconds, Δ indicates reading within 10 seconds, and × indicates that it takes 10 seconds or longer or cannot be read. Accordingly, it was found that when the reduction ratio is 4%, the reading performance is inferior, and when the reduction ratio is 2%, there is a problem in reading. Therefore, it was confirmed that the reduction ratio was at least 4% or more, preferably 5% or more, more preferably 6% or more.

  Next, the result of image superimposition using the QR code of the reduction module and the error diffusion image was verified. In the experiment, the QR code module is reduced with respect to the one that is simply overlapped with the error diffused by adding the module, and the size of one reduced module and one unit point area are made equal to what size It was verified whether it was readable. FIG. 13 shows a two-dimensional code image based on this.

As a result, the obtained two-dimensional code image is obtained by simply superimposing the QR code on the error-diffused design image when the module reduction ratio is 11.11% as shown in FIG. 13 (FIG. 13A). Compared with, in the error diffusion, the module with the addition of the error diffusion (FIG. 13B) can clearly recognize the entire face visually. Similarly, when the reduction ratio is 6.25%, the error diffusion is performed by adding the reduction module in the error diffusion as compared with the case where the QR code is simply superimposed on the error diffusion design image (FIG. 13C). In FIG. 13D, the entire face can be recognized more clearly. Further, in the case of a reduction rate of 4.00%, the error diffusion with the addition of the reduction module (FIG. 13 (f)) is more error-differing than that (FIG. 13 (e)). The face image is beautiful, but the QR code reading result of the reduction module is not good. Table 2 shows the results of reading these QR codes, which are two-dimensional code images. Therefore, it can be said that the reduction ratio is at least 6% or more, preferably 6% or more, and the smaller the dot area size is, the smaller the size of the dot module, the clearer the synthesized image can be obtained.

  Next, an example of the quaternary error diffusion QR code described based on FIG. 11 of the above embodiment will be described. When the QR code is superimposed on the normal image shown in FIG. 10A by this quaternary error diffusion method, as shown in FIG. 14, a two-dimensional code image with a smoother gradation expression is obtained. Could be formed. Therefore, it was confirmed that the quaternary error diffusion method is effective for superimposing such a two-dimensional code and a normal image.

10 QR code 11 Module 11a Black module 11b White module 12 Function pattern area 14 Encoding area 15 Reduction module 16 Margin area 18 Point area

Claims (6)

In a two-dimensional code image generation method for superimposing a normal image, which is an image that can be viewed with an arbitrary design, in an image of a two-dimensional code displayed in black and white,
The black and white modules constituting the two-dimensional code are reduced to form a reduction module, and the two-dimensional code is formed by the reduction module,
Forming a margin area around the individual reduced modules where the reduced modules are not displayed;
The normal image is regarded as a collection of minute point areas having a predetermined luminance, and at least a fixed luminance value of white or black is given to each point area of the display area of the two-dimensional code, and the normal image is superimposed. Forming an image of the display area of the two-dimensional code, and performing error diffusion processing for each point area to determine the fixed luminance value of the point area,
In the margin area of the display area of the two-dimensional code by the reduction module, the normal image composed of a collection of the point areas set to the fixed luminance value is overlaid,
In the arrangement position of the reduction module in the display area of the two-dimensional code, when setting the fixed luminance value of the point area at that position, the luminance value of the reduction module is set to that point regardless of the luminance value of the normal image. The error diffusion process is performed to determine the fixed luminance value of the region and diffuse the difference between the determined fixed luminance value and the error-diffused luminance value at the position to the surrounding point region as the next error. A method of generating a two-dimensional code image, wherein the fixed luminance value of the point area is determined, and a two-dimensional code image is formed by superimposing the two-dimensional code image on the normal image.   The two-dimensional code image generation method according to claim 1, wherein a difference in size between the point area and the reduction module is formed within 20% of each other.   3. The two-dimensional code image generation method according to claim 2, wherein the size of the point area and the reduction module are equal.   2. The two-dimensional image according to claim 1, wherein the error diffusion process forms a black and white binary point and an intermediate gray fixed luminance value point by the point area and superimposes the two-dimensional code on the normal image. Code image generation method.   5. The two-dimensional code image generation according to claim 1, wherein the two-dimensional code is a QR code, and the reduction module sets an area ratio of 20% or less of the module before reduction and 5% or more. Method. A two-dimensional code image in which a normal image, which is a normal design image, is superimposed on a two-dimensional code displayed in black and white binary;
The black and white modules constituting the two-dimensional code are reduced to form a reduction module, and the two-dimensional code is formed by the reduction module,
Forming a margin area around the individual reduced modules where the reduced modules are not displayed;
The normal image is regarded as a collection of minute point regions having a predetermined luminance, and at least a fixed luminance value of white or black is given to each point region of the display region of the two-dimensional code, and the normal image is obtained. Forming an image of the superimposed display area of the two-dimensional code, performing error diffusion processing for each point area, determining the fixed luminance value of the point area;
In the margin area of the display area of the two-dimensional code by the reduction module, the normal image composed of a collection of the point areas set to the fixed luminance value is overlaid,
In the arrangement position of the reduction module in the display area of the two-dimensional code, when setting the fixed luminance value of the point area at that position, the luminance value of the reduction module is set to that point regardless of the luminance value of the normal image. The error diffusion process is performed to determine the fixed luminance value of the region and diffuse the difference between the determined fixed luminance value and the error-diffused luminance value at the position as a next error to the surrounding point region. A two-dimensional code image obtained by determining the fixed luminance value of a point area and superimposing the image of the two-dimensional code on the normal image.