Information processing device, information processing method, and computer program

Abstract

An information processing device 1 comprises: an acquisition unit 11 for acquiring a captured pattern image PI of ridges of a living body; an estimation unit 12 for setting a sampling point in the pattern image PI and estimating an interval of the ridges in the sampling point; and a normalization unit 13 for normalizing the size of the pattern image PI on the basis of the estimated result of the estimation unit 12.

Description

[Technical Field]

[0001] The present disclosure relates to the technical fields of an information processing device, an information processing method, and a recording medium. [Background technology]

[0002] Patent Document 1 describes a technology that contributes to improving matching accuracy by extracting minutiae and skeletons from a first striped pattern image and a second striped pattern image in which stripes are formed by ridges, generating minutiae data and skeleton data, matching two sets of minutiae data and skeleton data extracted from the first striped pattern image and the second striped pattern image, respectively, to calculate a matching score, analyzing the second striped pattern image for an area in which opposing minutiae pairs exist in the first striped pattern image to calculate an image analysis score, and correcting the matching score. Patent Document 2 describes a technology that enlarges a specific fingerprint image, generates enrollment data including information about the enlarged fingerprint image, stores the generated enrollment data in a memory unit, and authenticates the fingerprint by matching the enrollment data stored in the memory unit with data related to the fingerprint input for matching. Patent document 3 describes a technology in which fingerprint information to be registered is input, the number and spacing of ridges in a specified area is extracted from the input fingerprint information, and based on the extracted number and spacing of ridges, the input fingerprint information is classified into one of multiple groups defined according to the degree of density of the fingerprint, and the group thus classified is associated with the input fingerprint information and registered. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] International Publication No. 2021 / 192315 [Patent Document 2] International Publication No. 2007 / 141880 [Patent Document 3] Japanese Patent Application Laid-Open No. 2006-039777 Summary of the Invention [Problem to be solved by the invention]

[0004] An object of this disclosure is to provide an information processing device, an information processing method, and a recording medium that aim to improve upon the techniques described in prior art documents. [Means for solving the problem]

[0005] One aspect of the information processing device includes an acquisition means for acquiring a pattern image obtained by capturing an image of a ridge of a living body, an estimation means for setting sampling points within the pattern image and estimating the ridge spacing of the sampling points, and a normalization means for normalizing the size of the pattern image based on the estimation result by the estimation means.

[0006] One aspect of the information processing method includes an acquisition means for acquiring a pattern image obtained by capturing an image of a ridge of a living body, an estimation means for setting sampling points within the pattern image and estimating the ridge spacing of the sampling points, and normalizing the size of the pattern image based on the estimation results by the estimation means.

[0007] In one embodiment of the recording medium, a computer program is recorded on a computer to execute an information processing method including: an acquisition means for acquiring a pattern image obtained by capturing an image of a ridge of a living body; an estimation means for setting sampling points within the pattern image and estimating the ridge spacing at the sampling points; and normalizing the size of the pattern image based on the estimation results by the estimation means. [Brief explanation of the drawings]

[0008] [Figure 1] FIG. 1 is a block diagram showing the configuration of an information processing device according to the first embodiment. [Figure 2] FIG. 2 is a block diagram showing the configuration of an information processing device according to the second embodiment. [Figure 3] FIG. 3 is a flowchart showing the flow of information processing operations performed by the information processing device in the second embodiment. [Figure 4] FIG. 4 is a conceptual diagram of the information processing operation of the information processing device in the second embodiment. [Figure 5] FIG. 5 is a conceptual diagram of the information processing operation of the information processing device in the second embodiment. [Figure 6] FIG. 6 is a conceptual diagram of a modified example of the second embodiment. [Figure 7] FIG. 7 is a block diagram showing the configuration of an information processing device according to the third embodiment. [Figure 8] FIG. 8 is a flowchart showing the flow of information processing operations performed by the information processing device in the third embodiment. [Figure 9] FIG. 9 is a conceptual diagram of the information processing operation of the information processing device in the third embodiment. [Figure 10] FIG. 10 is a block diagram showing the configuration of an information processing device according to the fourth embodiment. [Figure 11] FIG. 11 is a flowchart showing the flow of information processing operations performed by the information processing device in the fourth embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0009] Hereinafter, embodiments of an information processing device, an information processing method, and a recording medium will be described with reference to the drawings. [1: First embodiment]

[0010] An information processing device, an information processing method, and a recording medium according to a first embodiment will be described below. The information processing device, the information processing method, and the recording medium according to the first embodiment will be described below using an information processing device 1 to which the information processing device, the information processing method, and the recording medium according to the first embodiment are applied. [1-1: Configuration of information processing device 1]

[0011] The configuration of an information processing device 1 in the first embodiment will be described with reference to Fig. 1. Fig. 1 is a block diagram showing the configuration of the information processing device 1 in the first embodiment.

[0012] As shown in FIG. 1, the information processing device 1 includes an acquisition unit 11, an estimation unit 12, and a normalization unit 13. The acquisition unit 11 acquires a pattern image PI obtained by capturing an image of ridges of a living body. The estimation unit 12 sets sampling points within the pattern image PI and estimates the ridge spacing of the sampling points. The normalization unit 13 normalizes the size of the pattern image PI based on the estimation result by the estimation unit 12. [1-2: Technical Effects of Information Processing Device 1]

[0013] The information processing device 1 in the first embodiment can acquire a pattern image with a normalized size, and therefore can improve the success rate of matching when matching pattern images with each other, for example. [2: Second embodiment]

[0014] A second embodiment of an information processing device, an information processing method, and a recording medium will be described below. Hereinafter, the second embodiment of the information processing device, the information processing method, and the recording medium will be described using an information processing device 2 to which the second embodiment of the information processing device, the information processing method, and the recording medium is applied.

[0015] In fingerprint matching, ridge pattern matching is often performed. For example, even if the fingerprints belong to the same person, matching may fail if the ridge pattern sizes are different. For example, when matching a fingerprint image registered in childhood with a fingerprint image captured after adulthood, the fingerprint image matching may fail due to the difference in ridge pattern sizes, even though the ridge patterns are similar.

[0016] Fingerprint matching was originally used primarily to identify criminals, so it was often not intended to be used with children. In recent years, fingerprint matching has come to be used for personal authentication, and there has been an increase in the number of cases where children's fingerprints are matched. There are also cases where fingerprint images registered as a child are used to authenticate the individual as an adult.

[0017] Furthermore, for example, when fingerprint images of the same person's fingers captured at different resolutions are compared, the size of the ridge pattern will differ. Even if the ridge pattern is the same, if the ridge pattern size is different, for example, the coordinate distribution of fingerprint minutiae may differ, and fingerprint image matching may fail. There is a great demand for fingerprint matching using fingerprint images of different sizes.

[0018] Furthermore, engines that extract ridges and feature values ​​from fingerprint images PI and perform matching of fingerprint images PI are often constructed to be optimal for ridge patterns of a predetermined size. For example, even when matching adult images captured at 500 ppi, the size of the ridge patterns will be different. Even if the ridge patterns are the same, if the ridge pattern sizes are different, for example, the coordinate distribution of fingerprint minutiae may be different, and matching of fingerprint images may fail. There is a great demand for fingerprint matching using fingerprint images of different sizes. Furthermore, engines that extract ridges and feature values ​​from fingerprint images PI and perform matching of fingerprint images PI are often constructed to be optimal for ridge patterns of a predetermined size. For example, if the ridges and feature values ​​from the fingerprint image PI of an adult image captured at 500 ppi are different, matching of fingerprint images may fail. Lottery In some cases, the engine is designed to be optimal for matching fingerprint images PI of adults captured at 500 ppi and 500 ppi. Nosa Preferably, the ridge pattern is normalized to the desired size.

[0019] Finger size and the spacing between ridges are often correlated. For example, finger size varies greatly between infants and adults. On the other hand, the ridge pattern of an infant's fingerprint often remains unchanged even after the individual becomes an adult. In other words, it can be considered that the spacing between ridges changes as the finger size changes. In fact, compared to the ridges of adults, the spacing between ridges of children is often narrower and the ridge pitch is finer. Therefore, the information processing device 2 in the second embodiment may normalize the size of the fingerprint image PI based on the spacing between ridges. [2-1: Configuration of information processing device 2]

[0020] The configuration of the information processing device 2 in the second embodiment will be described with reference to Fig. 2. Fig. 2 is a block diagram showing the configuration of the information processing device 2 in the second embodiment.

[0021] 2, the information processing device 2 includes a calculation device 21 and a storage device 22. The information processing device 2 may further include a communication device 23, an input device 24, and an output device 25. However, the information processing device 2 does not necessarily include at least one of the communication device 23, the input device 24, and the output device 25. The calculation device 21, the storage device 22, the communication device 23, the input device 24, and the output device 25 may be connected via a data bus 26.

[0022] The arithmetic device 21 includes, for example, at least one of a central processing unit (CPU), a graphics processing unit (GPU), and a field programmable gate array (FPGA). The arithmetic device 21 reads a computer program. For example, the arithmetic device 21 may read a computer program stored in the storage device 22. For example, the arithmetic device 21 may read a computer program stored in a computer-readable, non-transitory recording medium using a recording medium reading device (e.g., an input device 24 described later) not shown in the drawings that is provided in the information processing device 2. The arithmetic device 21 may acquire (i.e., download or read) the computer program from a device (not shown) located outside the information processing device 2 via the communication device 23 (or another communication device). The arithmetic device 21 executes the read computer program. As a result, logical functional blocks for executing operations to be performed by the information processing device 2 are realized within the arithmetic device 21. That is, the arithmetic device 21 can function as a controller for realizing logical functional blocks for executing the operations (in other words, processing) that the information processing device 2 should perform.

[0023] 2 shows an example of logical functional blocks implemented in the arithmetic device 21 to perform information processing operations. As shown in FIG. 2, implemented in the arithmetic device 21 are an acquisition unit 211 which is a specific example of "acquisition means," an estimation unit 212 which is a specific example of "estimation means," a normalization unit 213 which is a specific example of "normalization means," a first setting unit 214 which is a specific example of "first setting means," and a second setting unit 215 which is a specific example of "second setting means." However, the information processing device 2 does not necessarily have to include at least one of the first setting unit 214 and the second setting unit 215. The operations of the acquisition unit 211, the estimation unit 212, the normalization unit 213, the first setting unit 214, and the second setting unit 215 will be described later with reference to FIGS. 3 to 5.

[0024] The storage device 22 can store desired data. For example, the storage device 22 may temporarily store a computer program executed by the arithmetic device 21. The storage device 22 may temporarily store data that the arithmetic device 21 temporarily uses when the arithmetic device 21 is executing a computer program. The storage device 22 may store data that the information processing device 2 stores long-term. The storage device 22 may include at least one of a RAM (Random Access Memory), a ROM (Read Only Memory), a hard disk device, a magneto-optical disk device, an SSD (Solid State Drive), and a disk array device. In other words, the storage device 22 may include a non-temporary recording medium.

[0025] The communication device 23 is capable of communicating with devices external to the information processing device 2 via a communication network (not shown). The communication device 23 may acquire a fingerprint image PI to be used in the information processing operation from, for example, an imaging device via the communication network.

[0026] The input device 24 is a device that accepts information input to the information processing device 2 from outside the information processing device 2. For example, the input device 24 may include an operation device (for example, at least one of a keyboard, a mouse, and a touch panel) that can be operated by an operator of the information processing device 2. For example, the input device 24 may include a reading device that can read information recorded as data on a recording medium that can be externally attached to the information processing device 2.

[0027] The output device 25 is a device that outputs information to the outside of the information processing device 2. For example, the output device 25 may output information as an image. That is, the output device 25 may include a display device (a so-called display) that can display an image showing the information to be output. For example, the output device 25 may output information as sound. That is, the output device 25 may include an audio device (a so-called speaker) that can output sound. For example, the output device 25 may output information on paper. That is, the output device 25 may include a printing device (a so-called printer) that can print desired information on paper. [2-2: Information processing operation performed by information processing device 2]

[0028] The flow of information processing authentication operation performed by the information processing device 2 in the second embodiment will be described with reference to Fig. 3 to Fig. 5. Fig. 3 is a flowchart showing the flow of information processing operation performed by the information processing device 2 in the second embodiment. Figs. 4 and 5 are conceptual diagrams of the information processing operation of the information processing device 2 in the second embodiment.

[0029] The acquiring unit 211 acquires a pattern image obtained by capturing an image of ridges of a living body (step S20). The living body may be a finger, and the pattern image may be a fingerprint image PI including a pattern area PA formed by ridges of the finger. The acquiring unit 211 may acquire a fingerprint image PI obtained by capturing an image of ridges of the living body. For example, the acquiring unit 211 may acquire a fingerprint image PI as shown in FIG. 4(a) as an example.

[0030] The first setting unit 214 sets a rectangular area RA within the fingerprint image PI (step S21). The first setting unit 214 may estimate a pattern area PA within the fingerprint image PI and set the rectangular area RA. For example, the first setting unit 214 may set a rectangular area RA as shown in FIG. 4(b). Note that, for ease of viewing, the pattern is omitted from FIGS. 4(b) to 4(d).

[0031] The second setting unit 215 sets a sampling point SP within the rectangular area RA of the fingerprint image PI using the center C of the rectangular area RA as a reference point (step S22). The second setting unit 215 may extract the center C of the rectangular area RA as the reference point, for example, as illustrated in FIG. 4(c).

[0032] The second setting unit 215 may set a sampling point SP in the fingerprint image PI on the fingertip side of the center C of the rectangular area RA. When a person places a finger on something, they often place the fingertip first. Therefore, if the sampling point SP is set on the fingertip side, the sampling point SP will often be set in the pattern area PA. Therefore, the second setting unit 215 may set a sampling point SP in the fingerprint image PI on the fingertip side of the center C of the rectangular area RA, as illustrated in FIG. 4(d), for example.

[0033] Ridge spacing may vary in different parts of the fingerprint image PI. For example, compare sampling points SP1 and SP3 with sampling points SP2 and SP4 shown in FIG. 5. In this case, sampling points SP1 and SP3 are set in an area where short ridges exist, so the ridge spacing at sampling points SP1 and SP3 is narrower than that at sampling points SP4 and SP5. Therefore, normalization of the fingerprint image PI based on information obtained from any one sampling point SP may not be appropriate. In contrast, normalization of the fingerprint image PI based on information obtained from multiple sampling points SP is often more appropriate. Therefore, the second setting unit 215 may set multiple sampling points SP.

[0034] The second setting unit 215 may set a plurality of sampling points SP at a plurality of positions that are the same distance from the reference point. For example, the second setting unit 215 may set four sampling points SP, as illustrated in FIG. 4(d).

[0035] For example, if sampling points are set in a horizontal line, there is a possibility that there will be areas where there is no fingerprint. Therefore, the second setting unit 215 may set multiple sampling points SP at multiple positions that are the same distance from the reference point. Since fingerprints are often oval in shape, setting sampling points SP in a fan shape that matches the oval shape, as shown in Figure 4(d), increases the possibility of setting sampling points SP in areas where there is a fingerprint.

[0036] The estimation unit 212 estimates the ridge intervals of the sampling points SP (step S23). For example, the estimation unit 212 may measure the number of ridges present in a predetermined section included in each of the multiple sampling points SP and estimate the ridge interval from the average of the measurement results. For example, as illustrated in FIG. 5, the estimation unit 212 may measure the number of ridges present in the predetermined section included in sampling point SP1 to be "3," the estimation unit 212 may measure the number of ridges present in the predetermined section included in sampling point SP2 to be "2," the estimation unit 212 may measure the number of ridges present in the predetermined section included in sampling point SP3 to be "3," and the estimation unit 212 may measure the number of ridges present in the predetermined section included in sampling point SP4 to be "2," and estimate the ridge interval based on the average of each measurement result, "2.5."

[0037] The normalization unit 213 normalizes the size of the fingerprint image PI based on the estimation result by the estimation unit 212 (step S24). The normalization unit 213 may estimate the size of the fingerprint image PI based on the estimated ridge spacing.

[0038] The normalization unit 213 may determine a scaling ratio based on the estimation result by the estimation unit 212, and normalize the size of the fingerprint image PI. The normalization unit 213 may determine the scaling ratio by comparing the average ridge spacing of a large number of fingerprint images registered in a database such as SD14 with the estimation result by the estimation unit 212. For example, the normalization unit 213 may use, as the scaling ratio, a value obtained by dividing the above-mentioned "average ridge spacing of a large number of fingerprint images" by the "ridge spacing" estimated by the estimation unit 212. In this way, the normalization unit 213 can convert the fingerprint image PI to an average size. [2-3: Variation]

[0039] Next, a modified example of the second embodiment will be described. In this modified example, when one sampling point SP is manually set by an administrator, the second setting unit 215 may automatically set each of multiple sampling points SP at multiple positions that are the same distance from the reference point as the manually set sampling point SP. Figure 6 is a conceptual diagram of the modified example of the second embodiment.

[0040] Fig. 6(a) illustrates a fingerprint image PI acquired by the acquisition unit 211. For example, as illustrated in Fig. 6(b), the administrator may manually set a sampling point SP0 in the fingerprint image PI. The setting operation from the administrator may be received by, for example, the input device 24. Note that, for ease of viewing, illustration of patterns is omitted in Figs. 6(b) to 6(d).

[0041] As illustrated in Fig. 6(c), the first setting unit 214 may set a rectangular area RA, and the second setting unit 215 may find positions at an equal distance from the center C of the rectangular area RA. The arcs shown by dashed lines in Fig. 6(c) indicate positions at an equal distance from the center C of the rectangular area RA.

[0042] 6(d), the second setting unit 215 may set the sampling point SPa1, the sampling point SPb, and the sampling point SPc at a plurality of positions that are the same distance from the center C. Also, as shown in FIG. 5(d), the second setting unit 215 may set the sampling point SPa1, the sampling point SPb, and the sampling point SPc within the fingerprint image PI on the fingertip side of the center C of the rectangular area RA.

[0043] In the second embodiment, the first setting unit 214 sets a rectangular area RA in the fingerprint image PI, but the shape of the area set in the fingerprint image PI is not limited to a rectangle. For example, the first setting unit 214 may set an elliptical area corresponding to the fingerprint shape in the fingerprint image PI.

[0044] Furthermore, in the second embodiment, the second setting unit 215 sets the sampling point SP in the fingerprint image PI on the fingertip side of the center C of the rectangular area RA, but the location where the sampling point SP is set is not limited to this. For example, if there is an area suitable for fingerprint authentication on the side of the fingerprint area PI that is farther from the fingertip than the center C of the rectangular area RA, the second setting unit 215 may set the sampling point SP in the area farther from the fingertip than the center C of the rectangular area RA.

[0045] The second setting unit 215 may also normalize the fingerprint image PI using at least one of the average ridge spacing and the ridge width. [2-4: Technical Effects of Information Processing Device 2]

[0046] The information processing device 2 in the second embodiment sets sampling points SP within the rectangular area RA of the fingerprint image PI using the center C of the rectangular area RA as a reference point, thereby increasing the possibility of setting sampling points SP in the pattern area PA. The information processing device 2 sets sampling points SP within the fingerprint image PI on the fingertip side of the center C of the rectangular area RA, thereby increasing the possibility of setting sampling points SP in an area with a closer fingerprint. The information processing device 2 sets multiple sampling points SP at multiple positions that are equally distant from the reference point, thereby enabling accurate estimation of ridge spacing. [3: Third embodiment]

[0047] An information processing device, an information processing method, and a recording medium according to a third embodiment will be described below. The third embodiment of the information processing device, the information processing method, and the recording medium will be described below using an information processing device 3 to which the third embodiment of the information processing device, the information processing method, and the recording medium is applied. [3-1: Configuration of information processing device 3]

[0048] The configuration of the information processing device 3 in the third embodiment will be described with reference to Fig. 7. Fig. 7 is a block diagram showing the configuration of the information processing device 3 in the third embodiment.

[0049] 7, the information processing device 3 of the third embodiment differs from the information processing device 2 of the second embodiment in that the calculation device 21 includes a matching unit 316 and the storage device 22 stores a fingerprint database DB in which registered pattern images are registered. However, the storage device 22 does not necessarily have to store a fingerprint database DB. Other features of the information processing device 3 may be the same as other features of the information processing device 2. [3-2: Information processing operation performed by information processing device 3]

[0050] The flow of the information processing authentication operation performed by the information processing device 3 in the third embodiment will be described with reference to Fig. 8. Fig. 8 is a flowchart showing the flow of the information processing operation performed by the information processing device 3 in the third embodiment.

[0051] The acquisition unit 211 acquires a pattern image obtained by capturing an image of ridges of a living body (step S20). The estimation unit 212 sets sampling points SP within the fingerprint image PI (step S22). The estimation unit 212 estimates the ridge spacing of the sampling points SP (step S23). The normalization unit 213 normalizes the size of the fingerprint image PI based on the estimation result by the estimation unit 212 (step S24).

[0052] The matching unit 316 matches the normalized pattern image N I , whose size has been normalized by the normalization unit 213, with a registered pattern image that has been registered in advance (step S30). The matching unit 316 may identify ridge portions from the normalized pattern image N I , whose size has been normalized, and generate a ridge image R I as useful fingerprint information. The matching unit 316 may match the ridge image R I with a registered pattern image that has been registered in advance. FIG. 9( a) illustrates an example of the normalized pattern image N I , and FIG. 9( b) illustrates an example of a ridge image R I in which ridge portions have been extracted from the normalized pattern image N I . The registered pattern image may include information on the ridge image from which the ridges have been extracted. The matching unit 316 may extract feature amounts from the normalized pattern image N I , whose size has been normalized, and compare it with a registered pattern image that has been registered in advance. The registered pattern image may include information on the feature amounts extracted from the registered pattern image. [3-3: Technical Effects of Information Processing Device 3]

[0053] For example, when fingerprint images PI of different sizes are compared, a high score may not be obtained and the comparison may fail, but when fingerprint images PI of the same size are compared, a high score may be obtained. The information processing device 3 in the third embodiment compares the normalized pattern image NI with a registered pattern image that has been registered in advance, thereby improving the probability of successful comparison. [4: Fourth embodiment]

[0054] An information processing device, an information processing method, and a recording medium according to a fourth embodiment will be described below. The information processing device, the information processing method, and the recording medium according to the fourth embodiment will be described below using an information processing device 4 to which the information processing device, the information processing method, and the recording medium according to the fourth embodiment are applied. [4-1: Configuration of information processing device 4]

[0055] The configuration of the information processing device 4 in the fourth embodiment will be described with reference to Fig. 10. Fig. 10 is a block diagram showing the configuration of the information processing device 4 in the fourth embodiment.

[0056] 10, the information processing device 4 in the fourth embodiment differs from the information processing device 2 in the second embodiment and the information processing device 3 in the third embodiment in that the arithmetic device 21 includes a registration unit 417 and the storage device 22 stores a fingerprint database DB in which registered pattern images are registered. However, the storage device 22 does not necessarily have to store a fingerprint database DB. Other features of the information processing device 4 may be the same as other features of at least one of the information processing device 2 and the information processing device 3. [4-2: Information processing operation performed by information processing device 4]

[0057] The flow of the information processing authentication operation performed by the information processing device 4 in the fourth embodiment will be described with reference to Fig. 11. Fig. 11 is a flowchart showing the flow of the information processing operation performed by the information processing device 4 in the fourth embodiment.

[0058] The acquisition unit 211 acquires a pattern image obtained by capturing an image of ridges of a living body (step S20). The estimation unit 212 sets sampling points SP within the fingerprint image PI (step S22). The estimation unit 212 estimates the ridge spacing of the sampling points SP (step S23). The normalization unit 213 normalizes the size of the fingerprint image PI based on the estimation result by the estimation unit 212 (step S24).

[0059] The registration unit 417 registers the normalized pattern image N I, whose size has been normalized by the normalization unit 213, in the storage device as a registered pattern image (step S40). The registration unit 417 may register the normalized pattern image N I, whose size has been normalized, in the fingerprint database DB of the storage device 22 as a registered pattern image. [4-3: Technical Effects of Information Processing Device 4]

[0060] The information processing device 4 in the fourth embodiment registers fingerprint images PI normalized to the same size, and therefore can reduce the processing load when matching fingerprint images PI. [5: Note]

[0061] The following additional notes are provided regarding the above-described embodiment. [Appendix 1] an acquisition means for acquiring a pattern image obtained by capturing an image of a ridge of a living body; an estimation means for setting sampling points within the pattern image and estimating ridge intervals at the sampling points; a normalization means for normalizing the size of the pattern image based on the estimation result by the estimation means; An information processing device comprising: [Appendix 2] a first setting means for setting a rectangular area within the pattern image; a second setting means for setting the sampling points within the rectangular area of ​​the pattern image using the center of the rectangular area as a reference point. 10. The information processing device according to claim 1. [Appendix 3] the pattern image is a fingerprint image, The second setting means sets the sampling point within the pattern image on the fingertip side from the center of the rectangular area. 3. The information processing device according to claim 2. [Appendix 4] The second setting means sets the plurality of sampling points at a plurality of positions that are equally distant from the reference point. 4. The information processing device according to claim 2 or 3. [Appendix 5] The image processing device further includes a comparison unit that compares a normalized pattern image, the size of which has been normalized by the normalization unit, with a registered pattern image that has been registered in advance. 5. The information processing device according to any one of appendices 1 to 4. [Appendix 6] The apparatus further comprises a registration means for registering the normalized pattern image, the size of which has been normalized by the normalization means, in a storage device as a registered pattern image. 6. The information processing device according to any one of appendices 1 to 5. [Appendix 7] an acquisition means for acquiring a pattern image obtained by capturing an image of a ridge of a living body; an estimation means for setting sampling points within the pattern image and estimating ridge intervals at the sampling points; The size of the pattern image is normalized based on the estimation result by the estimation means. Information processing methods. [Appendix 8] On the computer, an acquisition means for acquiring a pattern image obtained by capturing an image of a ridge of a living body; an estimation means for setting sampling points within the pattern image and estimating ridge intervals at the sampling points; The size of the pattern image is normalized based on the estimation result by the estimation means. A recording medium on which a computer program for executing an information processing method is recorded.

[0062] At least some of the constituent elements of each of the above-described embodiments can be appropriately combined with at least some of the other constituent elements of each of the above-described embodiments. Some of the constituent elements of each of the above-described embodiments may not be used. 。

[0063] This disclosure may be modified as appropriate within the scope of the claims and the technical idea that can be read from the entire specification. Information processing devices, information processing methods, and recording media that involve such modifications are also included in the technical idea of ​​this disclosure. [Explanation of symbols]

[0064] 1,2,3,4 Information processing equipment 11,211 Acquisition Department 12,212 Estimation section 13,213 Normalization part 214 First Setting Section 215 Second Setting Section 316 Collation Unit 417 Registration Department PI Fingerprint Image RA rectangular area C center SP Sampling Point NI normalized pattern image RI ridge image

Claims

1. an acquisition means for acquiring a pattern image obtained by capturing an image of a ridge of a living body; a first setting means for setting a rectangular area within the fingerprint image, which is the pattern image; a second setting means for setting a sampling point in the fingerprint image in an area closer to the fingertip than a horizontal line passing through the center point of the rectangular area; an estimation means for estimating the ridge intervals of the sampling points; a normalization means for determining a scaling ratio of the pattern image based on the estimation result by the estimation means and normalizing the size of the pattern image; An information processing device comprising:

2. The second setting means sets each of a plurality of sampling points on a sector-shaped arc centered on the center point of the rectangular area. The information processing device according to claim 1 .

3. The image processing device further includes a comparison unit that compares a normalized pattern image, the size of which has been normalized by the normalization unit, with a registered pattern image that has been registered in advance.

3. The information processing device according to claim 1 or 2.

4. The apparatus further comprises a registration means for registering the normalized pattern image, the size of which has been normalized by the normalization means, in a storage device as a registered pattern image.

3. The information processing device according to claim 1 or 2.

5. A pattern image of the ridges of a living body is acquired, A rectangular area is set within the fingerprint image, which is the pattern image; a sampling point is set in the fingerprint image in an area on the fingertip side of a horizontal line passing through the center point of the rectangular area; Estimating the ridge spacing of the sampling points; A scaling ratio of the pattern image is determined based on the result of the estimation, and the size of the pattern image is normalized. A computer-implemented information processing method.

6. Setting the sampling points includes setting each of a plurality of sampling points on a sector-shaped arc centered on a center point of the rectangular area. The information processing method according to claim 5 .

7. On the computer, A pattern image of the ridges of a living body is acquired, A rectangular area is set within the fingerprint image, which is the pattern image; a sampling point is set in the fingerprint image in an area on the fingertip side of a horizontal line passing through the center point of the rectangular area; Estimating the ridge spacing of the sampling points; A scaling ratio of the pattern image is determined based on the result of the estimation, and the size of the pattern image is normalized. A computer program for executing an information processing method.

8. Setting the sampling points includes setting each of a plurality of sampling points on a sector-shaped arc centered on a center point of the rectangular area.

8. A computer program according to claim 7.

Images