Identification information detection device and identification information detection program

Abstract

To provide an identification information detection apparatus capable of detecting identification information with high accuracy, and a program for detecting identification information.SOLUTION: An identification information detection apparatus includes: an image sensor 16; a lens 15 which is arranged so that the light reflected by a surface of a target object pass through the center when the light is radiated in a direction normal to the surface of the target object having the surface with irregularities serving as identification information formed thereon; a multi-wavelength coaxial aperture filter 17 which is arranged between the lens 15 and the image sensor 16; image data acquisition means which acquires image data based on signals obtained from pixels of the image sensor, in the case where the target object is irradiated with the light in the direction normal to the surface, when the light diffusely reflected by the irregularities reaches the image sensor through the multi-wavelength coaxial aperture filter; and conversion means which converts the image data obtained by the image data acquisition means into identification information.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention relates to an identification information detection device and an identification information detection program. [Background technology]

[0002] Traditionally, identification information detection has been used to determine authenticity. There are two methods for determining authenticity: analog, in which an experienced person appraises a product and determines its authenticity based on their experience, and digital, in which a specific ID or mark is attached to the product and the ID or mark is used to determine its authenticity using hardware or software.

[0003] These IDs and marks can be obtained by embedding an IC tag, printing the mark itself, or attaching it later with adhesive or other methods. By attaching identification information to products in this way, it becomes possible to identify individual products, and by utilizing dedicated hardware and software for the identification information such as IDs and marks, it becomes possible to recognize individual products. The devices used for such purposes are strictly dedicated devices and cannot be used for other purposes.

[0004] Patent document 1 discloses an identification device that determines the authenticity of an article to which an anti-counterfeiting medium is attached, using the anti-counterfeiting medium in which the observed light pattern changes depending on the optical characteristics of the light that is irradiated. This device includes a similarity calculation unit that calculates the similarity between multiple captured image data of the anti-counterfeiting medium, in which the light characteristics of the irradiated light are different, and correct image data corresponding to the light characteristics, and an authenticity determination unit that determines whether the anti-counterfeiting medium is correct by determining whether the similarity calculated for each light characteristic exceeds a threshold value set corresponding to each of the light characteristics.

[0005] Patent Document 2 discloses an authentication determination application and an authentication determination system that enable easy authentication. The authentication determination application of this invention is configured to extract shading information from a photographed image of a marking member imported into a user terminal, compare it with shading determination information previously incorporated into the application to evaluate consistency, and control the user terminal to determine that the marking member is authentic if the consistency is found. Information related to the object, including a predetermined hidden mark, is laser-engraved onto the marking member in advance, and at least one of the size, depth, and position of the laser engraving is a basic setting that varies for each user. The shading determination information includes reference shading information and hidden mark position information calculated in accordance with the laser engraving processing information based on relationship data between the size and depth of the laser engraving and the brightness of the photographed image of the laser engraving. The application is unique for each user because it incorporates different shading determination information for each user. Non-Patent Document 1 also discloses an imaging technology that can instantly capture clear images of minute defects. [Prior art documents] [Patent documents]

[0006] [Patent Document 1] International Publication No. 2017 / 159608 [Patent Document 2] International Publication No. 2023 / 286390 [Non-patent literature]

[0007] [Non-Patent Document 1] Hiroshi Ohno and two others, "Imaging technology that can instantly capture clear images of minute defects," Toshiba Review Vol. 76 No. 6 (November 2021 issue) pp. 38-41 Summary of the Invention [Problem to be solved by the invention]

[0008] The embodiments of the present invention provide an identification information detection device and an identification information detection program that can detect identification information with high accuracy. [Means for solving the problem]

[0009] An identification information detection device according to an embodiment of the present invention comprises an image sensor, a lens arranged so that when light is irradiated from a direction directly facing a surface of an object having a surface on which concave and convex portions serving as identification information are formed, light reflected by the surface passes through the center of the surface, a multi-wavelength coaxial aperture filter arranged between the lens and the image sensor, image data acquisition means for acquiring image data based on signals obtained from each pixel of the image sensor when light is irradiated onto the object from a direction directly facing the surface and light diffused and reflected by the concave and convex portions reaches the image sensor via the multi-wavelength coaxial aperture filter, and a conversion means for converting the image data obtained by the image data acquisition means into identification information. In the identification information detection device, the conversion means obtains line number information corresponding to the number of lines of the concave and convex portions from the image data, and converts the line number information into identification information. It is characterized by:

[0010] In the identification information detection device according to an embodiment of the present invention, the conversion means converts image data of m rows and n columns obtained from each pixel of the image sensor into numerical values ​​of pixels of m rows and n columns to generate identification information.

[0011] In the identification information detection device according to an embodiment of the present invention, the conversion means obtains width, depth, and height information corresponding to the width, depth, and height of the uneven portion from the image data, and converts this width, depth, and height information into identification information to obtain the identification information.

[0013] In the identification information detection device according to an embodiment of the present invention, the conversion means obtains line width information caused by the uneven portion from the image data, and converts this width information and line number information into identification information.

[0014] In the identification information detection device according to an embodiment of the present invention, the conversion means obtains position information of the lines caused by the uneven portion from the image data, and converts this position information, line width information, and line number information into identification information.

[0015] In the identification information detection device according to an embodiment of the present invention, the conversion means obtains color information of the lines caused by the uneven portion from the image data, and converts this color information, position information, line width information, and line number information into identification information.

[0016] In the identification information detection device according to the embodiment of the present invention, the conversion means converts the image data into colored mark information to generate the identification information.

[0017] An identification information detection program according to an embodiment of the present invention includes an image sensor, a lens arranged so that when light is irradiated from a direction facing a surface of an object having a surface on which concave and convex portions serving as identification information are formed, light reflected by the surface passes through the center, and a multi-wavelength coaxial aperture filter arranged between the lens and the image sensor, and when light is irradiated onto the object from a direction facing the surface and light diffused and reflected by the concave and convex portions reaches the image sensor via the multi-wavelength coaxial aperture filter, image data is obtained based on signals obtained from each pixel of the image sensor, and the identification information is detected from this image data. The program causes a computer included in an identification information detection device to function as a conversion means for converting image data into identification information. In the identification information detection program, the computer is caused to function as the conversion means to obtain line number information corresponding to the number of lines formed by the concave-convex portion from the image data and convert this line number information into identification information. It is characterized by:

[0018] In the identification information detection program according to an embodiment of the present invention, the computer is caused to function as the conversion means to convert image data of m rows and n columns obtained from each pixel of the image sensor into numerical values ​​of pixels of m rows and n columns to obtain identification information.

[0019] In the identification information detection program according to an embodiment of the present invention, the computer is caused to function as the conversion means to obtain width, depth, and height information corresponding to the width, depth, and height of the uneven portion from the image data, and convert this width, depth, and height information into identification information.

[0021] In the program for detecting identification information according to an embodiment of the present invention, the computer is used as the conversion means to obtain line width information caused by the uneven portion from the image data, and convert this width information and line number information into identification information.

[0022] In the program for detecting identification information according to an embodiment of the present invention, the computer is used as the conversion means to obtain position information of the lines caused by the uneven portion from the image data, and convert this position information, line width information, and line number information into identification information.

[0023] In the program for detecting identification information according to an embodiment of the present invention, the computer is used as the conversion means to obtain color information of the lines caused by the uneven portion from the image data, and convert this color information, position information, line width information, and line number information into identification information.

[0024] In the identification information detection program according to the embodiment of the present invention, the computer is caused to function as the conversion means to convert the image data into colored mark information to generate identification information. [Brief explanation of the drawings]

[0025] [Figure 1] FIG. 1 is a diagram showing the structure of an optical system device used in an embodiment of the present invention. [Figure 2] 1 is a diagram showing a state of coloring from the light incident side of a multi-wavelength coaxial aperture filter to an image sensor in an optical system device used in an embodiment of the present invention. [Figure 3]1 is a diagram showing the configuration of an identification information detection device according to an embodiment of the present invention. [Figure 4] FIG. 2 is a block diagram of a means for realizing a program provided in an external storage device provided in the identification information detection device according to the embodiment of the present invention. [Figure 5] FIG. 2 is a diagram showing a pixel arrangement of an image sensor provided in the identification information detection device according to the embodiment of the present invention. [Figure 6] 10 is a diagram showing an example of the relationship between light incident on a surface of an object and the color of scattered light generated at an uneven portion during operation of the identification information detection device according to the embodiment of the present invention. [Figure 7] 1 is a plan view of a multi-wavelength coaxial aperture filter with a unique color arrangement design, used in an identification information detection device according to an embodiment of the present invention. [Figure 8] 4A and 4B are diagrams showing examples of reflected light when light is irradiated onto an uneven portion from above by an identification information detection device according to an embodiment of the present invention. [Figure 9] 1 is a diagram showing the optical path of reflected light when light is irradiated onto an uneven portion from above, until the reflected light forms an image on an image sensor, using an identification information detection device according to an embodiment of the present invention. [Figure 10] 10 is a diagram showing the path of reflected light from an uneven portion formed by a plurality of parallel linear scratches, detected by an identification information detection device according to an embodiment of the present invention; [Figure 11] Plan view of an uneven area consisting of three scratches of the same width. [Figure 12] 12 is a diagram showing an image of an image obtained when the uneven portion of FIG. 11 is imaged. [Figure 13] A plan view of an uneven area consisting of three scratches of different widths. [Figure 14] 14 is a diagram showing an image obtained when the uneven portion of FIG. 13 is imaged. FIG. [Figure 15] 10 is a diagram showing an example of a mark with colored circles superimposed thereon, obtained when an image of a concave-convex portion is captured by an image sensor used in an identification information detection device according to an embodiment of the present invention. FIG. DETAILED DESCRIPTION OF THE INVENTION

[0026] An identification information detection device and an identification information detection program according to an embodiment of the present invention will be described below with reference to the accompanying drawings. In each drawing, the same components are given the same reference numerals, and duplicate explanations will be omitted. The inventors of the present application have invented the "OneShot BRDF optical inspection technology (an imaging technology that can instantly produce a clear image of minute defects)" (see Non-Patent Document 1), which will be described below, and have decided to apply this to an embodiment of the present invention.

[0027] The construction and principle of OneShot BRDF (Bidirectional Reflectance Distribution Function) uses a telecentric optical system as the optical system used for imaging. A telecentric optical system lens provides the same magnification regardless of the distance or position of an object in the field of view. The impression of spatial depth in the image is flat, so objects at two different working distances appear to be the same size.

[0028] The structure of a OneShot BRDF optical system (optical system device) 100 is as shown in Figure 1. That is, for example, light emitted from an LED 11 is collimated by an illumination lens 12, and is then irradiated from the front (direction facing) onto the plane of an object 14 by a beam splitter 13. The light reflected by the plane of the object 14 is imaged on an image sensor 16 via an imaging lens 15 that passes through the center. A multi-wavelength coaxial aperture filter 17 is placed on the focal plane between the imaging lens 15 and the image sensor 16.

[0029] The multi-wavelength coaxial aperture filter 17 is a filter with concentric colors that separates the BRDF of reflected light by color. With the optical system device 100, light (specularly reflected light) that enters the illumination lens 12 straight from a flat, defect-free surface passes through the color at the center of the multi-wavelength coaxial aperture filter 17, and if there is a defect (uneven portion 18), light (scattered light) that enters the illumination lens 12 at an angle passes through the color on the outside of the multi-wavelength coaxial aperture filter 17, allowing an image to be captured in which the defect is colored. Figure 2 shows the coloring of the multi-wavelength coaxial aperture filter 17 from the light entrance side to the image sensor 16 in this case.

[0030] An identification information detection device according to an embodiment of the present invention can be configured using a computer, as shown in Fig. 3. That is, a CPU 20 configures the identification information detection device using programs and data in a main memory 21. An external storage interface 23, an input interface 24, a display interface 25, and a data input interface 26 are connected to the CPU 20 via a bus 22.

[0031] An external storage device 33 is connected to the external storage interface 23. The external storage device 33 stores programs and data for the operation of this identification information detection device, which the CPU 20 can read into the main memory 21 as needed for use. For this reason, as shown in FIG. 4, the external storage device 33 stores programs for implementing the image data acquisition means 3 and the conversion means 4. An input device 34 such as a keyboard or touch panel and a pointing device 32 such as a mouse are connected to the input interface 24. A display device 35 having a screen such as an LCD is connected to the display interface 25. The image sensor 16 of the optical system device 100 is connected to the data input interface 26, and signals obtained from each pixel of the image sensor 16 are digitized and input by the data input interface 26. The digital signals obtained by the data input interface 26 are input by the CPU 20 and processed to detect identification information.

[0032] In this embodiment, the image data acquisition means 3 and conversion means 4 provided in the external storage device 33 have the following functions: When light is irradiated from a direction directly facing the surface of the object 14 having a surface on which an uneven portion 18 serving as identification information is formed, the image data acquisition means 3 acquires image data based on signals obtained from each pixel of the image sensor 16 when the light is diffusely reflected by the uneven portion 18 and reaches the image sensor 16 via the multi-wavelength coaxial aperture filter 17.

[0033] Assume that the image sensor 16 has, for example, m (positive integer) rows and n (positive integer) columns of photoelectric conversion elements (pixels), and outputs color signal values ​​(e.g., voltages) corresponding to the m rows and n columns of pixels as shown in Fig. 5. Correspondingly, the image data acquisition means 3 converts the color signal values ​​into image data of a required gradation. Here, the image data can be expressed in L (positive integer) gradations corresponding to wavelengths from blue to red, for example, and the L gradations can be expressed in k bits.

[0034] The conversion means 4 converts the image data obtained by the image data acquisition means 3 into identification information. The conversion means 4 converts, for example, image data of m rows and n columns obtained from each pixel of the image sensor 16 into numerical values ​​of the pixels of m rows and n columns to obtain identification information. That is, all numerical values ​​of the pixels of m rows and n columns, in which L gradations are expressed in k bits, are converted into one piece of identification information. In this embodiment, the identification information is basically numbers, letters, etc., but may also be an image mark, etc.

[0035] The conversion means 4 is configured taking into consideration the following characteristics and properties of the optical system device 100. A feature of the optical system device 100 is that the scattering angle of the scattered light (BRDF) of the object changes depending on the depth and height of the unevenness 18 on the object, and the scattered light angle can be expressed by mathematical parameters relative to the depth and height of the unevenness. The scattered light generated by the unevenness 18 is collected by the imaging lens 15 using an optical mechanism, and color-separated by the multi-wavelength coaxial aperture filter 17, a characteristic of OneShot BRDF, before reaching the image sensor 16 and being captured. Figure 6 shows an example of the relationship between the light incident on the surface of the object 14 and the color of the scattered light generated by the unevenness 18. The scattering angle changes depending on the height and depth of the unevenness 18 on the object 14.

[0036] In this case, the color of the scattered light captured by the multi-wavelength coaxial aperture filter 17 is artificially changed depending on the height and depth of the uneven portion 18, thereby adjusting the m-row, n-column image data obtained from each pixel of the image sensor 16. In other words, by using the multi-wavelength coaxial aperture filter 17 having a predetermined color scheme, the m-row, n-column image data obtained by capturing the scattered light generated by uneven portions 18 of the same height and depth will be the same image data, and the identification information obtained by converting this image data will be the same identification information. Therefore, the conversion means 4 of the first embodiment obtains depth-height information corresponding to the depth and height of the uneven portion 18 from the image data, and converts this depth-height information into identification information to obtain the identification information.

[0037] By designing the multi-wavelength coaxial aperture filter 17 with a unique color arrangement, light scattered at a scattering angle according to the height and depth of the uneven portion 18 can be captured as an image with a predetermined color arrangement. Figure 7 shows a plan view of the multi-wavelength coaxial aperture filter 17 with a unique color arrangement design. In this multi-wavelength coaxial aperture filter 17, the center is red, the outside of the red is blue, the outside of the blue is green, and the outside of the green is yellow. Note that there is a pink color between red and blue, and a light blue between blue and green.

[0038] Next, consider the relationship between the height and depth of the uneven portion 18 and the identification information. Assume that there is an object with uneven portions 18 of different heights and depths, as shown in Figures 8(a), 8(b), and 8(c). When light is irradiated from above onto the uneven portions 18 of Figures 8(a), 8(b), and 8(c), reflected light is generated, and the scattering angle at this time is unique depending on the height and depth of the uneven portion 18. It can be seen that the uneven portion 18, including the case of a U-shaped groove having a width d as shown in Figure 8(d), has a unique scattering angle and scattering range corresponding to the width, depth, and height of the uneven portion 18, and predetermined image data can be obtained from the uneven portion 18 of a predetermined width, depth, and height. Therefore, the conversion means 4 of the second embodiment obtains width, depth, and height information corresponding to the width, depth, and height of the uneven portion 18 from the image data, and converts this width, depth, and height information into identification information to obtain the identification information.

[0039] For example, an object having uneven portions 18 formed thereon with various widths, depths, and heights as identification information is used to obtain image data (for example, numerical values ​​of pixels in m rows and n columns, with L gradations expressed in k bits), and a table is created to which corresponding identification information (such as character strings) is assigned, and stored in the external storage device 33. When detecting the identification information, image data is obtained from the uneven portions 18 of the object by the image data obtaining means 3, and the conversion means 4 performs conversion using the table to obtain the identification information.

[0040] Next, let us consider the relationship between the height and depth of the uneven portion 18, as well as the color of the multi-wavelength coaxial aperture filter 17 through which light passes, and the identification information. Assume an object with uneven portions 18 of different heights and depths, as shown in Figures 9(a), 9(b), and 9(c). As in Figure 8, in Figure 9, when light is irradiated onto the uneven portion 18 from above, reflected light is generated, and the scattering angle at this time is unique depending on the height and depth of the uneven portion 18. In Figures 9(a), 9(b), and 9(c), due to the different scattering angles, the light is incident on different positions on the multi-wavelength coaxial aperture filter 17, and is colored differently before reaching the image sensor 16 and being imaged. As a result, it is possible to obtain image data of different colors due to the different depths and heights of the uneven portion 18. Therefore, the conversion means 4 of the third embodiment obtains width, depth, height, and color information corresponding to the width, depth, and height of the uneven portion 18 from the image data, and converts this width, depth, height, and color information into identification information to obtain the identification information.

[0041] For example, for an object on which uneven portions 18 having various widths, depths, and heights are formed as identification information, image data (for example, numerical values ​​of pixels in m rows and n columns, in which L gradations including color are expressed in k bits) is obtained using a multi-wavelength coaxial aperture filter 17 with a predetermined color arrangement, and a table in which corresponding identification information (such as character strings) is assigned is created and stored in the external storage device 33. When detecting the identification information, image data is obtained from the uneven portions 18 of the object by the image data acquisition means 3, and the conversion means 4 performs conversion using the table to obtain the identification information.

[0042] Next, consider the case where the uneven portion 18 is composed of multiple parallel linear scratches. Consider the case where the uneven portion 18 is composed of multiple parallel linear scratches 19A, 19B, and 19C as shown in FIG. 10. These scratches 19A, 19B, and 19C have different depths and heights, as shown in the plan view of FIG. 11. The image formed by the uneven portion 18 is red, blue, and green lines, as shown in FIG. 12. In this case, the image data is obtained as numerical values ​​for m rows and n columns of pixels, where L gradations including color are expressed in k bits. That is, in this fourth embodiment, the color information for red, blue, and green and the position information for these lines are expressed as numerical values ​​where L gradations are expressed in k bits. The conversion means 4 obtains these numerical values ​​and converts the color information and position information to generate identification information. That is, if there is a line segment in which red, blue, and green are aligned at a predetermined position, red is assigned a numerical value of "1," blue is assigned a numerical value of "2," and green is assigned a numerical value of "3." Since the position information of the line is red → blue → green, the numerical values ​​are arranged in the order of the position information and converted into identification information 123. Furthermore, if there is a line segment in which red, green, and blue are arranged at a predetermined position, the conversion means 4 converts this image data into identification information 132 according to the same rule as above. In the fourth embodiment, too, image data is obtained in advance, a table in which corresponding identification information is assigned is created, and stored in the external storage device 33, and conversion can be performed using this. In this case, the position information may be obtained by counting the number of pixels from the position information start position shown in Figure 12, or by counting the number of pixels upward and to the right from point O in Figure 12 and obtaining the (x, y) coordinates.

[0043] As shown in Fig. 13, scratches 19A, 19B, and 19C may have different widths to provide variations in the identification information. The image created by such uneven portion 18 will have red, blue, and green lines of different widths, as shown in Fig. 14. In this case, width information may be created by counting the number of pixels as described with reference to Figs. 11 and 12, and conversion may be performed so that different identification information is assigned to line segments arranged in red, green, and blue with different numbers of pixels in width.

[0044] Furthermore, the conversion means 4 according to the fifth embodiment can be configured to capture, as a line, a linear set of pixels represented by pixels having approximately the same numerical value within an upper and lower limit range in pixel data consisting of m rows and n columns, with L gradations expressed in k bits. The conversion means 4 obtains line number information corresponding to the number of lines in the concave and convex portions from the image data, and converts this line number information into identification information. In this case, even if the lines are made up of different colors, they are still considered to be one line.

[0045] Furthermore, the conversion means 4 according to the sixth embodiment may be configured to capture, as a line, a linear set of pixels represented by pixels with similar numerical values ​​within an upper and lower limit range in pixel data composed of pixel values ​​arranged in m rows and n columns, with L gradations expressed in k bits, and also to obtain width information of the lines caused by uneven portions from the image data. This allows the conversion means 4 to obtain the width information of the lines caused by uneven portions from the image data, and convert this width information and information on the number of lines into identification information. That is, the identification information includes information such as how many lines have width F1, how many lines have width F2, how many lines have width F3, etc.

[0046] Next, in the seventh embodiment, in addition to the configuration of the sixth embodiment, the conversion means 4 can be configured to obtain position information of the lines caused by the concave and convex portions from the image data, and convert this position information, line width information, and line number information into identification information to be used as the identification information. That is, the identification information may include information such as how many lines of width F1 are located in the first and fourth positions from the beginning, how many lines of width F2 are located in the second and fifth positions from the beginning, how many lines of width F3 are located in the third and sixth positions from the beginning, etc. Furthermore, this may be combined with line color information to be used as the identification information.

[0047] Next, in the eighth embodiment, the conversion means 4 converts the image data obtained by the image data acquisition means 3 into colored mark information to be used as identification information. For example, as shown in Fig. 15, it is assumed that an uneven portion 18 is attached to an object, and a mark M with a colored circle superimposed thereon is imaged by the image sensor 16. It is assumed that this mark M is an uneven portion 18 with the outermost portion pink, the inner portion blue, the inner portion green, and the innermost portion red, and each position and the radius of the circle are predetermined.

[0048] Even in this case, the image data acquisition means 3 obtains, as image data, the numerical values ​​of pixels in m rows and n columns, where L gradations are expressed in k bits, from the signal obtained by the image sensor 16. The conversion means 4 converts the pixels in m rows and n columns, where L gradations are expressed in k bits, back into marks M (image) shown in Fig. 15. The conversion means 4 has a table for converting L gradations into k-bit data into color pixels, and performs the conversion using this table.

[0049] As described above, according to this embodiment, different images are obtained depending on the scattering angle, and these images are captured by an image sensor to serve as identification information. This makes it possible to detect uneven portions as identification information with high precision, at a resolution of several μm. Therefore, marks made of uneven portions that are indistinguishable by humans can be recognized. In this case, the specific color scheme and central diameter of the multi-wavelength coaxial aperture filter are the key to detecting the identification information, enabling accurate detection of unique identification information.

[0050] Therefore, the invention of this embodiment can be used for inspections such as authenticity determination. For example, by providing an inspection object that needs to be authenticated in advance with concave and convex portions of a required height and depth, and then capturing an image of the object using an image sensor through a multi-wavelength coaxial aperture filter with a specific color scheme to obtain identification information, it is not possible to obtain the same identification information unless an object with concave and convex portions of the same height and depth is imaged, making it possible to determine authenticity. [Explanation of symbols]

[0051] 3. Image data acquisition method 4 Conversion methods 11 LED 12 Lighting lenses 13 Beam splitter 14 Object 15 Imaging lens 16 Image Sensors 17 Multi-wavelength coaxial aperture filter 18 Uneven part 19A, 19B, 19C scratches 20 CPU 21 Main Memory 22 Bus 23 External Memory Interface 24 input interfaces 25 Display Interface 26 Data Entry Interface 32 Pointing Device 33 External storage device 34 Input Devices 35 Display device 100 Optical equipment

Claims

1. An image sensor; a lens arranged so that when light is irradiated from a direction directly facing a surface of an object having a surface on which concave and convex portions serving as identification information are formed, light reflected by the surface passes through the center of the lens; a multi-wavelength coaxial aperture filter disposed between the lens and the image sensor; an image data acquisition means for acquiring image data based on signals obtained from each pixel of the image sensor when light is irradiated onto the object from a direction facing the surface and the light is diffusely reflected by the uneven portion and reaches the image sensor via the multi-wavelength coaxial aperture filter; a conversion means for converting the image data obtained by the image data acquisition means into identification information, The identification information detection device is characterized in that the conversion means obtains line number information corresponding to the number of lines caused by the uneven portion from the image data, and converts this line number information into identification information to obtain the identification information.

2. 2. The identification information detection device according to claim 1, wherein said conversion means converts image data of m rows and n columns obtained from each pixel of said image sensor into numerical values ​​of pixels of m rows and n columns to obtain identification information.

3. 2. The identification information detection device according to claim 1, wherein the conversion means obtains width, depth, and height information corresponding to the width, depth, and height of the uneven portion from the image data, and converts this width, depth, and height information into identification information.

4. 2. The identification information detection device according to claim 1, wherein the conversion means obtains width information of the lines caused by the uneven portion from the image data, and converts this width information and information on the number of lines into identification information.

5. The identification information detection device according to claim 4, characterized in that the conversion means obtains position information of lines caused by the uneven portion from the image data, and converts this position information, line width information, and line number information into identification information.

6. The identification information detection device according to claim 5, characterized in that the conversion means obtains color information of the lines caused by the uneven portion from the image data, and converts this color information, position information, line width information, and line number information into identification information.

7. 2. The identification information detecting device according to claim 1, wherein said conversion means converts said image data into colored mark information to obtain the identification information.

8. An image sensor; a lens arranged so that when light is irradiated from a direction directly facing a surface of an object having a surface on which concave and convex portions serving as identification information are formed, light reflected by the surface passes through the center of the lens; a multi-wavelength coaxial aperture filter disposed between the lens and the image sensor; Equipped with a computer provided in an identification information detection device that, when light is irradiated onto the object from a direction facing the surface, the light diffused and reflected by the uneven portion reaches the image sensor via the multi-wavelength coaxial aperture filter, obtains image data based on signals obtained from each pixel of the image sensor, and detects identification information from this image data; An identification information detection program that functions as a conversion means for converting image data into identification information, A program for detecting identification information, characterized in that the computer is used as the conversion means to obtain line number information corresponding to the number of lines caused by the uneven portion from the image data, and convert this line number information into identification information to form the identification information.

9. 9. The program for detecting identification information according to claim 8, wherein the computer is caused to function as the conversion means to convert image data of m rows and n columns obtained from each pixel of the image sensor into numerical values ​​of pixels of m rows and n columns to obtain identification information.

10. The identification information detection program according to claim 8, characterized in that the computer is made to function as the conversion means to obtain width, depth, and height information corresponding to the width, depth, and height of the uneven portion from the image data, and convert this width, depth, and height information into identification information.

11. The identification information detection program according to claim 8, characterized in that the computer is made to function as the conversion means to obtain line width information caused by the uneven portion from the image data, and convert this width information and line number information into identification information.

12. The identification information detection program according to claim 11, characterized in that the computer is configured to function as the conversion means to obtain position information of lines caused by the uneven portion from the image data, and convert this position information, line width information, and line number information into identification information.

13. The identification information detection program according to claim 12, characterized in that the computer is made to function as the conversion means to obtain color information of the lines caused by the uneven portion from the image data, and convert this color information, position information, line width information, and line number information into identification information.

14. 9. The identification information detection program according to claim 8, wherein the computer is caused to function as the conversion means to convert the image data into colored mark information to generate the identification information.

Images