Information processing device, information processing method, and recording medium

Abstract

This information processing device includes: an extraction means for extracting a plurality of feature points from a pattern image; a classification means for classifying the plurality of feature points into a plurality of clusters; a generation means for generating a fragmented image from the pattern image on the basis of the plurality of clusters; and an output means for outputting the fragmented image.

Description

Information processing device, information processing method, and recording medium

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

[0002] Patent Document 1 describes a technology in which the coordinate position of each search fingerprint feature point contained in the search fingerprint data is replaced with the coordinate position of a coordinate system based on a coordinate reference point contained in the file fingerprint data, and the search fingerprint feature points located around the coordinate reference point and the group of file fingerprint feature points included in the file fingerprint data are checked for the presence or absence of any singular points scattered within a coordinate range near the coordinate reference point specified in the fingerprint matching parameters, a zone check of the coordinate range near the coordinate reference point, and a quality check of the group of feature points located within the coordinate range near the coordinate reference point, and the like, to determine whether to use the axis matching method or the position alignment matching method.

[0003] Japanese Patent Application Laid-Open No. 2004-265038

[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 disclosed in prior art documents.

[0005] One aspect of the information processing device includes an extraction means for extracting a plurality of feature points from a pattern image, a classification means for classifying the plurality of feature points into a plurality of clusters, a generation means for generating a fragmented image from the pattern image based on the plurality of clusters, and an output means for outputting the fragmented image.

[0006] One aspect of the information processing method extracts a plurality of feature points from a pattern image, classifies the plurality of feature points into a plurality of clusters, generates a fragmented image from the pattern image based on the plurality of clusters, and outputs the fragmented image.

[0007] In one aspect of the recording medium, a computer program is recorded to cause a computer to execute an information processing method for extracting a plurality of feature points from a pattern image, classifying the plurality of feature points into a plurality of clusters, generating a fragmented image from the pattern image based on the plurality of clusters, and outputting the fragmented image.

[0008] FIG. 1 is a block diagram showing an example of the configuration of an information processing device according to the present disclosure. FIG. 2 is a block diagram showing an example of the configuration of an information processing device according to the present disclosure. FIG. 3 is a flowchart showing an example of the information processing operation of an information processing device according to the present disclosure. FIG. 4 is a conceptual diagram showing an example of the information processing operation of an information processing device according to the present disclosure. FIG. 5 is a block diagram showing an example of the configuration of an information processing device according to the present disclosure. FIG. 6 is a block diagram showing an example of the configuration of an information processing device according to the present disclosure.

[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] A first embodiment of an information processing device, an information processing method, and a recording medium will be described below. Hereinafter, the first embodiment of the information processing device, the information processing method, and the recording medium will be described using an information processing device 1 according to this disclosure. [1-1: Configuration of Information Processing Device 1]

[0011] 1 is a block diagram showing the configuration of an information processing device 1 according to this disclosure. As shown in FIG. 1, the information processing device 1 includes an extraction unit 11, a classification unit 12, a generation unit 13, and an output unit 14.

[0012] The extraction unit 11 extracts a plurality of feature points from the pattern image. The classification unit 12 classifies the plurality of feature points into a plurality of clusters. The generation unit 13 generates a fragmented image from the pattern image based on the plurality of clusters. The output unit 14 outputs the fragmented image.

[0013] In this disclosure, a print image is an image of a print that includes multiple feature points. A print image is an image that can be acquired from a living body, and includes at least one of a fingerprint, a palm print, and a footprint. [1-2: Technical Effects of Information Processing Device 1]

[0014] The information processing device 1 according to this disclosure generates a fragmented image based on clusters of feature points. As a result, the information processing device 1 can include meaningful areas of the pattern image in the fragmented image. Because the fragmented image is generated based on clusters of feature points, it is unlikely to include meaningless areas, such as areas that do not include feature points. The information processing device 1 can increase the amount of meaningful areas of the pattern image that are included in the area included in the fragmented image. [2: Second embodiment]

[0015] 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 an information processing device, an information processing method, and a recording medium will be described using an information processing device 2 according to this disclosure. [2-1: Configuration of Information Processing Device 2]

[0016] 2 is a block diagram showing the configuration of the information processing device 2. As shown in FIG. 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 have to 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.

[0017] The arithmetic device 21 includes, for example, at least one of a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), and an FPGA (Field Programmable Gate Array). 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 included 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. In other words, the arithmetic device 21 can function as a controller for realizing logical functional blocks for executing operations (in other words, processes) to be performed by the information processing device 2. The arithmetic device 21 may output information to devices (not shown), such as other computers or cloud servers, that are provided outside the information processing device 2, via the communication device 23 (or other communication devices).

[0018] FIG. 2 shows an example of logical functional blocks implemented within the computing device 21 to perform information processing operations. As shown in FIG. 2 , the computing device 21 includes an extraction unit 211, which is a specific example of an “extraction means” described in the appendix, a classification unit 212, which is a specific example of a “classification means” described in the appendix, a generation unit 213, which is a specific example of a “generation means” described in the appendix, an output unit 214, which is a specific example of an “output means” described in the appendix, an acquisition unit 215, and a reception unit 216, which is a specific example of a “reception means” described in the appendix. However, at least one of the acquisition unit 215 and the reception unit 216 may not be implemented within the computing device 21. Details of the operations of the extraction unit 211, classification unit 212, generation unit 213, output unit 214, acquisition unit 215, and reception unit 216 will be described later with reference to FIG. 3 .

[0019] 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.

[0020] 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 be a communication interface based on standards such as Ethernet (registered trademark), Wi-Fi (registered trademark), Bluetooth (registered trademark), or USB (Universal Serial Bus).

[0021] 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 (e.g., 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.

[0022] 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 the Information Processing Device 2]

[0023] The information processing operation performed by the information processing device 2 will be described with reference to Fig. 3. Fig. 3 is a flowchart showing an example of the flow of the information processing operation performed by the information processing device 2.

[0024] As shown in Fig. 3A, the acquisition unit 215 acquires a pattern image (step S20). The acquisition unit 215 may acquire a pattern image stored in the storage device 22. Alternatively, the acquisition unit 215 may acquire the pattern image from an external device via the communication device 23. The extraction unit 211 extracts a plurality of feature points from the acquired pattern image (step S21). Fig. 4A illustrates an example of a plurality of feature points x extracted from the pattern image PI.

[0025] The receiving unit 216 receives the designation of the predetermined number (n) (step S22). The receiving unit 216 may receive the designation of the predetermined number (n) input by the user to the input device 24. The operation of step S22 may be performed before step S20. The operation of step S22 is not an essential operation in one information processing operation, and may not be performed in some cases. For example, when the user checks information related to feature points extracted from the pattern image and recognizes that designation is necessary, the receiving unit 216 may receive the input of the designation of the predetermined number (n).

[0026] Each of the feature points included in the pattern image can form a cohesive group, i.e., a cluster. The classification unit 212 classifies the feature points into a plurality of clusters (step S23). The feature points classified into a cluster are called feature points belonging to the cluster. Details of the operation of step S23 will be described with reference to FIG. 3(b).

[0027] 3(b), the classification unit 212 determines the number of clusters (C) to be classified from the number (N) of extracted feature points and a predetermined number so that each of the plurality of clusters contains a predetermined number (n) of feature points (step S23-1). The classification unit 212 may determine the number of clusters (C) by dividing the number (N) of extracted feature points by the predetermined number (n). In other words, if the pattern image contains a relatively large number of feature points, the classification unit 212 classifies the pattern image into a relatively large number of clusters. On the other hand, if the pattern image contains a relatively small number of feature points, the classification unit 212 classifies the pattern image into a relatively small number of clusters.

[0028] The classification unit 212 selects C feature points as initial representative points (step S23-2). The classification unit 212 may select the initial representative points randomly. Alternatively, the classification unit 212 may select feature points that are appropriately separated from each other as initial representative points.

[0029] The classification unit 212 repeats a first operation (step S23-3) of classifying the plurality of feature points into C clusters each including n feature points centered on a representative point, and a second operation (step S23-4) of selecting a new representative point from each of the C classified clusters. The classification unit 212 may repeat the first and second operations until the classified clusters become cohesive and meaningful groups (step S23-5: yes). Figure 4(b) illustrates a plurality of feature points x classified into five clusters C1, C2, C3, C4, and C5.

[0030] The generation unit 213 generates fragmented images from the pattern image based on the multiple clusters (step S24). The generation unit 213 generates multiple fragmented images corresponding to each of the multiple clusters. The generation unit 213 generates fragmented images so as to include feature points belonging to the corresponding clusters. The generation unit 213 generates fragmented images according to the distribution of each of the feature points belonging to the corresponding clusters. In other words, the generation unit 213 generates fragmented images corresponding to clusters so as to reduce areas where feature points included in the clusters are not distributed. FIG. 4(c) illustrates fragmented images I1, I2, I3, I4, and I5 generated from the pattern image based on five clusters C1, C2, C3, C4, and C5. The shapes of the fragmented images will be described in other embodiments.

[0031] The generation unit 213 may generate a segmented image based on the distance between the representative point of the cluster and each of the feature points belonging to the cluster. The representative point of the cluster may be a feature point located at the center of the cluster, or may be a feature point located at the center of gravity of the cluster. Alternatively, the representative point of the cluster may be a position where no feature point exists.

[0032] The output unit 214 outputs the fragmented image (step 25). The output unit 214 may control a display as the output device 25 to display the fragmented image. The output unit 214 may control the storage device 22 to store the fragmented image in the storage device 22. The output unit 214 may control the communication device 23 to transmit the fragmented image to an external device. [2-3: Modifications]

[0033] The information processing device 2 may be configured to allow the number of fragmented images required to be specified. In this case, the receiving unit 216 may receive a specification of the desired number (C) of fragmented images. The receiving unit 216 may receive a specification of the desired number (C) input by the user to the input device 24. When the number of fragmented images required is specified, the number of feature points contained in the fragmented images also changes depending on the number of feature points contained in the pattern image. [2-4-1: Necessity of Fragmented Images 1]

[0034] Machine learning is used for image enhancement processing, feature extraction processing, etc. in fingerprint matching. Machine learning requires a large amount of training data.

[0035] Fingerprints may be matched using fragmentary fingerprint images, such as latent fingerprint images, which show only a partial region of the entire fingerprint, rather than fingerprint images that include the entire fingerprint, such as imprint fingerprint images. When machine learning is used for various processes in latent fingerprint matching, a large amount of learning data of fragmentary fingerprint images is required. However, there are not many samples of fragmentary fingerprint images that are useful for machine learning. For example, fragmentary fingerprint images of regions that do not include minutiae are not useful for matching, and are not useful for machine learning either. Therefore, for example, fragmentary fingerprint images obtained by randomly dividing an imprint fingerprint are often not useful for machine learning. The information processing device 2 disclosed herein is useful for mass-generating fragmentary fingerprint images that are useful for machine learning.

[0036] Furthermore, latent fingerprint images often contain information other than fingerprints. For this reason, the information processing device 2 may synthesize other images with different shading as backgrounds to prepare fragmented fingerprint images that resemble latent fingerprints, as learning data used in machine learning for various processes in matching latent fingerprints. [2-4-2: Necessity of Fragmented Images 2]

[0037] Compared to fingerprint images, palm print images are larger in size and have more feature points to be detected. The more feature points there are, the higher the matching cost becomes. Furthermore, because palm print images have a wide distribution of feature points, they are susceptible to image distortion. This makes it difficult, for example, to overlay the entire palm print image. Thus, matching the entire palm print image is difficult. Furthermore, the entire palm print image often contains areas that are difficult to use for matching.

[0038] By generating a fragmented palmprint image, the number of feature points extracted from individual images can be reduced, thereby lowering the matching cost. Furthermore, by including areas useful for matching palmprint images in the fragmented palmprint image, the effects of distortion can be suppressed, important information is not missed, and unnecessary matching can be reduced. The information processing device 2 disclosed herein is useful for generating a fragmented palmprint image that includes areas useful for matching palmprint images. [2-5: Technical Effects of Information Processing Device 2]

[0039] The information processing device 2 according to this disclosure determines the shape of a fragmented image corresponding to a cluster based on at least one of the distance between the representative point of the cluster and each of the feature points belonging to that cluster and the shape of the distribution of each of the feature points belonging to the cluster, and is therefore able to generate a fragmented image that includes many meaningful areas that include feature points. The information processing device 2 can treat the areas included in each fragmented image as independently meaningful areas.

[0040] The information processing device 2 generates each fragmented image so that it contains a predetermined number of feature points, so that each fragmented image has the same amount of information. Since the number of feature points contained in a fragmented image or the number of fragmented images can be specified, the information processing device 2 can generate fragmented images with a desired amount of information. [3: Third Embodiment]

[0041] A third embodiment of an information processing device, an information processing method, and a recording medium 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 according to this disclosure. In the third embodiment, the operation of the generation unit 313 differs from that of the second embodiment. [3-1: Information processing operation performed by the information processing device 3]

[0042] The generating unit 313 generates an elliptical fragmented image. The generating unit 313 may determine the elliptical shape in accordance with the distribution of each of the feature points belonging to the cluster. The generating unit 313 may determine the elliptical shape based on the shape of the distribution of each of the feature points belonging to the cluster.

[0043] The generating unit 313 may determine the ellipse shape based on the distance between the representative point of the cluster and each of the feature points belonging to the cluster. For example, the generating unit 313 may determine a major axis based on the distance between the representative point of the cluster and each of the feature points belonging to the cluster corresponding to the representative point, and may generate a fragmented image corresponding to the cluster based on an ellipse that can be defined by this major axis. The generating unit 313 may determine the major axis of the ellipse based on the longest distance between the representative point of the cluster and each of the feature points belonging to the cluster corresponding to the representative point.

[0044] The generating unit 313 may generate a circular fragmented image. The generating unit 313 may determine the radius of the circle based on the longest distance between the representative point of the cluster and each of the feature points belonging to the cluster corresponding to the representative point. [3-2: Technical Effects of Information Processing Device 3] The information processing device 3 according to this disclosure generates a fragmented image corresponding to a cluster based on an ellipse whose major axis is determined based on the distance between the representative point of the cluster and each of the feature points belonging to the cluster corresponding to the representative point, and therefore can generate a fragmented image according to the shape of the distribution of each of the feature points belonging to the cluster. [4: Fourth Embodiment]

[0045] A fourth embodiment of an information processing device, an information processing method, and a recording medium will be described below. The fourth embodiment of the information processing device, the information processing method, and the recording medium will be described below using an information processing device 4 according to this disclosure. In the fourth embodiment, the operation of the generation unit 413 differs from the second and third embodiments. [4-1: Information processing operation performed by the information processing device 4]

[0046] The generating unit 413 generates a polygonal fragmented image. The polygon may be a convex polygon. The generating unit 413 may determine the polygonal shape according to the distribution of each of the feature points belonging to the cluster. The generating unit 413 may determine the polygonal shape based on the shape of the distribution of each of the feature points belonging to the cluster. The generating unit 413 may determine the polygonal shape based on the distance between the representative point of the cluster and each of the feature points belonging to the cluster. [4-2: Technical Effects of Information Processing Device 4]

[0047] The information processing device 4 according to this disclosure generates polygonal fragmented images, and therefore can generate fragmented images according to the shape of the distribution of each of the feature points belonging to a cluster. [5: Fifth Embodiment]

[0048] A fourth embodiment of an information processing device, an information processing method, and a recording medium will be described. A fifth embodiment of an information processing device, an information processing method, and a recording medium will be described below using an information processing device 5 according to this disclosure. The fifth embodiment differs from the second to fourth embodiments in that a determination unit 517 is implemented within the calculation device 21. [5-1: Information processing operation performed by the information processing device 5]

[0049] The determining unit 517 determines whether to make the fragmented image elliptical or polygonal in shape, depending on the distribution of each of the feature points belonging to the cluster. The determining unit 517 determines, for each of a plurality of clusters, whether to make the fragmented image corresponding to the cluster elliptical or polygonal.

[0050] The determination unit 517 may determine whether to make the fragmented image elliptical or polygonal in shape, depending on the distribution of each of the feature points belonging to the cluster. The determination unit 517 may determine whether to make the fragmented image elliptical or polygonal, based on the shape of the distribution of each of the feature points belonging to the cluster (referred to as the "distribution shape"). The determination unit 517 may determine which of a plurality of predetermined shapes the distribution shape is. The plurality of predetermined shapes includes an ellipse and a polygon including at least one of a triangle, a rectangle, a pentagon, and a hexagon. One of the plurality of predetermined shapes determined by the determination unit 517 is referred to as the "region shape." Alternatively, the determination unit 517 may determine whether to make the fragmented image elliptical or polygonal, based on the distance between the representative point of the cluster and each of the feature points belonging to the cluster.

[0051] Alternatively, the information processing device 5 may accept the region shape specified by the user who has confirmed the distribution shape.

[0052] The generation unit 513 generates a fragmented image of the region shape. The generation unit 513 may deform the region shape so that the region shape includes the region of the distribution shape and the region other than the region of the distribution shape is reduced, and generate a fragmented image of the deformed region shape.

[0053] The deformation of the region shape by the generation unit 513 may include enlarging or reducing the region shape. The deformation of the region shape by the generation unit 513 may include deformation that makes one of the sides of a polygon convex inward of the region shape. The deformation of the region shape by the generation unit 513 may include changing the length of at least one of the major axis and minor axis of an elliptical shape. [5-2: Technical Effects of the Information Processing Device 5]

[0054] The information processing device 5 according to this disclosure determines whether the shape of the fragmented image should be elliptical or polygonal, and can therefore generate a fragmented image according to the shape of the distribution of each of the feature points belonging to a cluster. [6: Supplementary Note]

[0055] The following supplementary notes are further disclosed in relation to the above-described embodiments. [Supplementary Note 1] An information processing device comprising: extraction means for extracting a plurality of feature points from a pattern image; classification means for classifying the plurality of feature points into a plurality of clusters; generation means for generating fragmented images from the pattern image based on the plurality of clusters; and output means for outputting the fragmented images. [Supplementary Note 2] The information processing device according to Supplementary Note 1, wherein each of the plurality of clusters includes a predetermined number of feature points from the plurality of feature points. [Supplementary Note 3] The information processing device according to Supplementary Note 2, wherein the information processing device comprises reception means for receiving designation of the predetermined number. [Supplementary Note 4] The information processing device according to Supplementary Note 1, wherein the generation means generates a plurality of the fragmented images corresponding to each of the plurality of clusters, and the fragmented images include feature points belonging to the corresponding cluster. [Supplementary Note 5] The information processing device according to Supplementary Note 1, wherein the generation means generates the fragmented image corresponding to each of the plurality of clusters in accordance with the distribution of each of the feature points belonging to the cluster. [Supplementary Note 6] The information processing device according to Supplementary Note 1, wherein the generation means generates a plurality of the fragmented images corresponding to each of the plurality of clusters based on the distance between a representative point of each of the plurality of clusters and each of the feature points belonging to each of the plurality of clusters. [Supplementary Note 7] The information processing device according to Supplementary Note 6, wherein the generation means generates the fragmented images corresponding to each of the clusters based on an ellipse whose major axis is determined based on the distance between the representative point and each of the feature points belonging to the cluster corresponding to the representative point. [Supplementary Note 8] The information processing device according to Supplementary Note 1, wherein the generation means determines the shape of the fragmented image corresponding to each of the plurality of clusters based on the shape of the distribution of each of the feature points belonging to the cluster. [Supplementary Note 9] The information processing device according to Supplementary Note 8, wherein the generation means generates the fragmented images in a polygonal shape. [Supplementary Note 10] The information processing device according to Supplementary Note 9, wherein the polygonal shape is a convex polygonal shape. [Supplementary Note 11] The information processing device according to Supplementary Note 5, further comprising: determination means for determining whether the shape of the fragmented images should be elliptical or polygonal. [Supplementary Note 12] The information processing device according to Supplementary Note 1, further comprising a receiving unit that receives a designation of a desired number of the fragmented images.[Supplementary Note 13] The information processing device according to Supplementary Note 1, wherein the pattern image includes at least one of a fingerprint image and a palm print image. [Supplementary Note 14] An information processing method comprising: extracting a plurality of feature points from a pattern image, classifying the plurality of feature points into a plurality of clusters, generating a fragmented image from the pattern image based on the plurality of clusters, and outputting the fragmented image. [Supplementary Note 15] A recording medium having recorded thereon a computer program for causing a computer to execute an information processing method comprising: extracting a plurality of feature points from a pattern image, classifying the plurality of feature points into a plurality of clusters, generating a fragmented image from the pattern image based on the plurality of clusters, and outputting the fragmented image.

[0056] Although this disclosure has been described above with reference to the embodiments, this disclosure is not limited to the above-described embodiments. Various modifications that can be understood by those skilled in the art can be made to the configuration and details of this disclosure within the scope of this disclosure. Furthermore, each embodiment can be combined with other embodiments as appropriate.

[0057] 1, 2, 3, 4, 5 Information processing device 11, 211 Extraction unit 12, 212 Classification unit 13, 213, 313, 413, 513 Generation unit 14, 214 Output unit 215 Acquisition unit 216 Reception unit 517 Determination unit

Claims

1. An information processing apparatus comprising: extraction means for extracting a plurality of feature points from a pattern image; classification means for classifying the plurality of feature points into a plurality of clusters; generation means for generating a fragmented image from the pattern image based on the plurality of clusters; and output means for outputting the fragmented image.

2. The information processing apparatus according to claim 1, wherein each of the plurality of clusters includes a predetermined number of the plurality of feature points.

3. The information processing apparatus according to claim 2, further comprising reception means for receiving the designation of the predetermined number.

4. The information processing apparatus according to claim 1, wherein the generation means generates a plurality of the fragmented images corresponding to each of the plurality of clusters, and the fragmented image includes feature points belonging to the corresponding cluster.

5. The information processing apparatus according to claim 1, wherein the generation means generates the fragmented image corresponding to each of the plurality of clusters according to the distribution of each of the feature points belonging to the cluster.

6. The information processing apparatus according to claim 1, wherein the generation means generates a plurality of the fragmented images corresponding to each of the plurality of clusters based on the distances between the representative points of each of the plurality of clusters and each of the feature points belonging to each of the plurality of clusters.

7. The information processing apparatus according to claim 6, wherein the generation means generates the fragmented image corresponding to the cluster based on an ellipse whose major axis is determined based on the distances between the representative point and each of the feature points belonging to the cluster corresponding to the representative point.

8. The information processing apparatus according to claim 1, wherein the generation means determines the shape of the fragmented image corresponding to each of the plurality of clusters based on the shape of the distribution of each of the feature points belonging to the cluster.

9. The information processing apparatus according to claim 8, wherein the generation means generates the fragmented image having a polygonal shape.

10. The information processing apparatus according to claim 9, wherein the polygonal shape is a convex polygonal shape.

11. The information processing apparatus according to claim 5, further comprising determination means for determining whether to make the shape of the fragmented image an elliptical shape or a polygonal shape.

12. The information processing apparatus according to claim 1, further comprising reception means for receiving the designation of a desired number of the fragmented images.

13. The information processing apparatus according to claim 1, wherein the pattern image includes at least one of a fingerprint image and a palmprint image.

14. An information processing method for extracting a plurality of feature points from a pattern image, classifying the plurality of feature points into a plurality of clusters, generating a fragmented image from the pattern image based on the plurality of clusters, and outputting the fragmented image.

15. A recording medium on which a computer program for causing a computer to execute an information processing method for extracting a plurality of feature points from a pattern image, classifying the plurality of feature points into a plurality of clusters, generating a fragmented image from the pattern image based on the plurality of clusters, and outputting the fragmented image is recorded.

Images