JP2006330873A - Fingerprint collation device, method and program - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a fingerprint collation device, method and a program capable of shortening a processing time. <P>SOLUTION: This fingerprint collation device is provided with: a fingerprint image input part 110 for capturing a collation fingerprint image as the object of collation; a pre-processing part 132 and a feature point extraction part 134 for extracting branch points and end points included in a ridge line included in the captured collation fingerprint image as feature points; a connection information generating part 136 for generating connection information showing the connection status of the branch points and end points included in the continuous ridge line; a characteristic pattern extraction part 138 for deciding functions for connecting each of the other branch points or end points adjacent along the ridge line in which the branch point under consideration is included with the branch point under consideration based on the connection information, and for extracting the combination of the functions corresponding to the branch point under consideration as a characteristic pattern; and a similarity decision processing part 140 for retrieving a registration fingerprint image similar to a collation fingerprint image or accessory information corresponding to the registration fingerprint image based on the characteristic pattern. <P>COPYRIGHT: (C)2007,JPO&INPIT

Description

  The present invention relates to a fingerprint collation apparatus, method, and program for extracting a registered fingerprint that matches an input fingerprint image.

In recent years, fingerprint authentication has been used as one method for preventing illegal use of a cash card of a financial institution or picking damage to a house. Fingerprint authentication is a technology that identifies the person corresponding to a registered fingerprint that matches the fingerprint image by comparing the fingerprint authentication data registered in advance with the feature data extracted from the input fingerprint image. There are various methods conventionally used (for example, refer to Patent Documents 1 and 2).
JP 2004-145447 A (page 2-11, FIG. 1-12) Japanese Patent Laying-Open No. 2004-5532 (page 2-11, FIG. 1-7)

  By the way, when fingerprint authentication technology is used for permission to enter a house, the number of registered fingerprints is not so large, but when fingerprint authentication is used for identity verification in financial institutions, the number of registered fingerprints is dramatic. As a result, the processing time becomes longer and the collation accuracy may be lowered. In addition, various fingerprint authentication techniques (eg, frequency analysis method, pattern matching method, minutia method, etc.) that have been used in the past are not perfect in terms of processing time and collation accuracy, and there is room for improvement. . Therefore, a fingerprint authentication technique that can replace or use these conventional methods is desired.

  The present invention was created in view of the above points, and an object thereof is to provide a fingerprint authentication apparatus, method, and program capable of shortening the processing time.

  In order to solve the above-described problem, a fingerprint collation apparatus according to the present invention includes a fingerprint image capturing unit that captures a collation fingerprint image to be collated, and a ridge included in the collation fingerprint image captured by the fingerprint image capturing unit. Alternatively, feature point extraction means for extracting branch points and end points included in valley lines as feature points, and connection information generation means for generating connection information indicating connection states of branch points and end points included in continuous ridges or valley lines Based on the connection information, paying attention to each branch point, each of the other branch points or end points adjacent to the branch line or valley line including the focused branch point, and the focused branch point And a feature pattern extraction means for extracting a combination of functions corresponding to the focused branch point as a feature pattern, and a feature pattern extraction means. It was based on the feature pattern, and a retrieving means for retrieving incidental information corresponding to the registered fingerprint image or the registered fingerprint image similar to the collation fingerprint image.

  The fingerprint collation method of the present invention includes a fingerprint image capture step for capturing a verification fingerprint image to be verified, and a branch included in a ridge or valley line included in the verification fingerprint image captured in the fingerprint image capture step. A feature point extraction step for extracting points and end points as feature points, a connection information generation step for generating connection information indicating a connection state between branch points and end points included in continuous ridges or valleys, and based on the connection information Focusing on each branch point, a function that connects each of the other branch points or end points adjacent to the branch line or valley line including the target branch point and the target branch point is determined. A feature pattern extraction step for extracting a combination of functions corresponding to the focused branch point as a feature pattern, and a feature pattern extraction step. It was based on the feature pattern, and a search step of searching for associated information corresponding to the registered fingerprint image or the registered fingerprint image similar to the collation fingerprint image.

  Further, the fingerprint collation program of the present invention is a feature point extraction unit that extracts a computer as a feature point using a branch point and an end point included in a ridge or valley line included in a collation fingerprint image captured by a fingerprint image capture unit. And the connection information generating means for generating connection information indicating the connection state between the branch points and the end points included in the continuous ridges or valleys, and focusing on each branch point based on the connection information. Determine the function that connects each of the other branch points or end points adjacent to the branch line along the ridge or valley line that includes the branch point and this focused branch point, and then select the combination of functions corresponding to this focused branch point. Feature pattern extraction means for extracting as a feature pattern, and a registered fingerprint similar to a verification fingerprint image based on the feature pattern extracted by the feature pattern extraction means To function as a retrieval means for retrieving the image or incidental information corresponding to the registered fingerprint image.

  The branch points and end points included in the ridges or valleys of the fingerprint are major features for identifying the fingerprint, and fingerprint matching is performed by using a feature pattern that indicates a combination of functions that connect these branch points and end points. It becomes possible. In particular, by using a feature pattern indicating such a combination of functions, it is possible to reduce the amount of information necessary for fingerprint collation and shorten the time required for collation processing.

  Further, the above-described function is a linear function, and the feature pattern is preferably a combination of the slopes of the straight lines indicated by the linear function. Thereby, the information amount of the feature pattern can be further reduced, and the processing time can be further shortened.

  Moreover, it is desirable that the slope of the straight line described above has a relative value for each branch point of interest. As a result, it is possible to remove the influence of the orientation at the time of capturing the collation fingerprint image, and the processing for correcting the orientation of the captured collation fingerprint image is not necessary, so that the processing can be simplified.

  Further, the image processing apparatus further includes a feature pattern storage unit in which a feature pattern corresponding to each of the plurality of branch points included in the registered fingerprint image is stored for each of the plurality of registered fingerprint images, and the search unit corresponds to the collation fingerprint image. It is desirable to perform the search process by comparing the feature pattern to be matched with the feature patterns corresponding to a plurality of registered fingerprint images stored in the feature pattern storage means. As a result, it is possible to easily search for similar registered fingerprint images by sequentially reading the feature patterns of the registered fingerprint images stored in advance and comparing them with the feature patterns of the verification fingerprint image, which is a comparison target. Even if there are many registered fingerprint images, the processing is not complicated and the processing can be simplified.

  In addition, when a feature pattern corresponding to a registered fingerprint image is acquired using the above-described fingerprint image capturing means, feature point extracting means, connection information generating means, and feature pattern extracting means, the feature pattern is stored as feature pattern storage means. It is desirable to further comprise a feature pattern storage processing means for storing in This makes it possible to add a registered fingerprint image to be verified as appropriate.

  Hereinafter, a fingerprint collation apparatus according to an embodiment to which the present invention is applied will be described in detail with reference to the drawings.

  FIG. 1 is a diagram illustrating a configuration of a fingerprint collation apparatus according to an embodiment. When a fingerprint image is input, the fingerprint collation apparatus shown in FIG. 1 searches for a registered fingerprint image (registered fingerprint image) similar to this image or accompanying information corresponding to this registered fingerprint image and outputs the search result. A fingerprint image input unit 110, a fingerprint DB (database) 120, a fingerprint collation processing unit 130, an operation unit 150, and a display unit 160.

  The fingerprint image input unit 110 is for taking a fingerprint image (a fingerprint image to be verified is referred to as a “verification fingerprint image”) into the fingerprint verification processing unit 130, and a fingerprint ridge (or an adjacent ridge) The fingerprint image data corresponding to the pattern of the valley line between the two is input. For example, a fingerprint image input unit 110 as an optical scanner that optically reads a ridge shape is used. As a result, it is only necessary to be able to read the ridge shape (or valley line shape) included in the fingerprint. Therefore, when the fingertip is pressed against the detection surface, the change in capacitance due to the contact of the fingerprint ridge is read. A fingerprint image may be acquired. Further, a fingerprint image may be acquired and input using various sensors other than these, or a fingerprint image already in a bitmap format or the like may be read by the fingerprint image input unit 110.

  The fingerprint DB 120 stores feature patterns extracted in correspondence with a plurality of fingerprint images (these images are referred to as “registered fingerprint images”) whose similarity is compared with the captured verification fingerprint image during the verification process. . A specific example of the feature pattern will be described later. The fingerprint DB 120 stores various accompanying information corresponding to each registered fingerprint image. For example, the accompanying information includes personal information (name, sex, address, etc.) corresponding to the registered fingerprint image. Prior to processing by the fingerprint collation processing unit 130, it is necessary to register the feature patterns of a plurality of registered fingerprint images in the fingerprint DB 120. Details of this registration process will be described later.

  The fingerprint collation processing unit 130 extracts a feature pattern of the captured collation fingerprint image and performs a process of searching for a registered fingerprint image similar to the collation fingerprint image based on the feature pattern. For this purpose, the fingerprint collation processing unit 130 includes a pre-processing unit 132, a feature point extraction unit 134, a connection information generation unit 136, a feature pattern extraction unit 138, a similarity determination processing unit 140, and a collation result output processing unit 142. Yes.

  The preprocessing unit 132 performs predetermined preprocessing on the collation fingerprint image captured using the fingerprint image input unit 110. For example, as preprocessing, processing for binarizing or thinning a captured fingerprint image is performed. The feature point extraction unit 134 extracts feature points included in the collation fingerprint image after the preprocessing by the preprocessing unit 132 is completed. Here, the feature points refer to the end points and branch points of the thinned ridges.

  FIG. 2 is a diagram illustrating a specific example of feature points included in the collation fingerprint image. The feature point extraction unit 134 extracts branch points and end points included in the collated fingerprint image after the preprocessing is completed, and assigns numbers in the order of extraction. This number is for identifying each feature point and may be in an appropriate order. In FIG. 2, the symbols of the branch points 1, 3, 4, 6 and the end points 2, 7, 10, 13 represent the numbers assigned by the feature point extraction unit 134 as they are. The collation fingerprint image shown in FIG. 2 includes other branch points and end points other than the branch points 1, 3, 4, 6 and the end points 2, 7, 10, 13, but in FIG. Description of signs (numbers) of branch points and end points is omitted.

  The connection information generation unit 136 generates connection information indicating a connection state between branch points and end points included in continuous ridges. FIG. 3 is a diagram showing specific contents of a concatenation table generated as concatenation information. In FIG. 3, numbers arranged in the horizontal direction and the vertical direction are numbers assigned to feature points (branch points or end points). For example, let us focus on a branch point 3 assigned number 3. As shown in FIG. 2, there are a branch point 4, a branch point 6, and an end point 10 as other feature points adjacent to the branch point 3 along the same ridge. In the connection table shown in FIG. 3, in the third row from the top corresponding to the branch point 3, the connection state is shown at the corresponding locations of the numbers 4, 6, and 10 corresponding to the branch point 4, the branch point 6, and the end point 10. The concatenation flag “1” is written. In this way, a concatenation table in which the concatenation flag “1” is written for each branch point or each end point is completed.

  The feature pattern extraction unit 138 extracts a feature pattern corresponding to each branch point based on the connection table (connection information) generated by the connection information generation unit 136. FIG. 4 is an explanatory diagram of a feature pattern. As described above, when focusing on the branch point 3, there are the branch point 4, the branch point 6, and the end point 10 as adjacent feature points along the same ridge, and these are connected by a linear function (primary function). Is shown in FIG. Specifically, the branch point 3 and the branch point 4 are connected by a straight line L1, the branch point 3 and the branch point 6 are connected by a straight line L2, and the branch point 3 and the end point 10 are connected by a straight line L3. . The feature pattern extraction unit 138 extracts a combination of the inclinations of these three straight lines L1, L2, and L3 as a feature pattern. Since the absolute inclination of each straight line is affected by the orientation of the collation fingerprint image captured by the fingerprint image input unit 110, in order to eliminate this influence, the relative inclination between adjacent straight lines, that is, The feature patterns are extracted by extracting three angles between adjacent straight lines and rearranging them in ascending order (or increasing order). Functions 1 to 3 included in the connection table of FIG. 3 indicate feature patterns formed by combinations of these three angles. In this way, the feature pattern extraction unit 138 extracts feature patterns corresponding to the branch points 1, 3, 4,... Included in the collation fingerprint image.

  The similarity determination processing unit 140 determines the similarity between the verification fingerprint image and each registered fingerprint image based on the feature pattern extracted corresponding to the verification fingerprint image, and a registered fingerprint image similar to the verification fingerprint image ( Or the accompanying information corresponding to this registered fingerprint image) is determined. The collation result output processing unit 142 displays the search result on the screen of the display unit 160 or prints the search result to a printing apparatus (not shown) when a printing operation using the operation unit 150 is performed. Instruct.

  By the way, the feature patterns (functions 1 to 3) included in the connection table shown in FIG. 3 are extracted based on the image data of the collation fingerprint image input from the fingerprint image input unit 110. In order to extract similar registered fingerprint images, it is necessary to extract feature patterns having the same contents for many registered fingerprint images in advance and register them in the fingerprint DB 120.

  FIG. 5 is a diagram showing a configuration of a database creation apparatus that performs feature pattern extraction on a registered fingerprint image in advance and registers it in the fingerprint DB 120. The configuration shown in FIG. 5 may be provided as a part of the fingerprint verification apparatus shown in FIG. 1, but may be constructed separately from the fingerprint verification apparatus shown in FIG. The database creation apparatus shown in FIG. 5 includes a fingerprint image input unit 210, a database creation unit 220, an operation unit 230, and a display unit 240 in order to register many feature patterns of registered fingerprint images in the fingerprint DB 120.

  The fingerprint image input unit 210 inputs image data indicating grayscale information for each pixel constituting the registered fingerprint image. Similar to the fingerprint image input unit 110 shown in FIG. 1, an optical scanner or other various sensors can be used as the fingerprint image input unit 210.

  The database creation unit 220 performs a process of extracting the feature pattern of the registered fingerprint image and registering it in the fingerprint DB 120. For this purpose, the database creation unit 220 includes a preprocessing unit 221, a feature point extraction unit 222, a connection information generation unit 223, a feature pattern extraction unit 224, and a file creation processing unit 225. Among these, the basic operations of the pre-processing unit 221 except the file creation processing unit 225, the feature point extraction unit 222, the connection information generation unit 223, and the feature pattern extraction unit 224 are the fingerprint collation processing unit 130 shown in FIG. The detailed description of the operation is omitted.

  The file creation processing unit 225 registers the extracted feature pattern for each registered fingerprint image in the fingerprint DB 120 as a set of files. The operation unit 230 is used to perform extraction of a feature pattern corresponding to a registered fingerprint image, an operation instruction necessary for registration, and the like. The operation unit 230 is used to input personal information as accompanying information corresponding to each registered fingerprint image. The display unit 240 is used for confirming registration contents of feature information and accompanying information and displaying various operation screens necessary for registration.

  By using the database creation device having such a configuration, it corresponds to a plurality of registered fingerprint image feature patterns and each registered fingerprint image having basically the same contents as the feature patterns included in the concatenation table shown in FIG. Accompanying information is registered in the fingerprint DB 120.

  The fingerprint image input units 110 and 210 described above are fingerprint image capturing means, the preprocessing units 132 and 221 and the feature point extraction units 134 and 222 are feature point extraction units, and the connection information generation units 136 and 223 are connection information generation units. The feature pattern extraction units 138 and 224 correspond to the feature pattern extraction unit, the similarity determination processing unit 140 corresponds to the search unit, the fingerprint DB 120 corresponds to the feature pattern storage unit, and the file creation processing unit 225 corresponds to the feature pattern storage processing unit, respectively. To do. The operations performed by the fingerprint image input units 110 and 210 are the operations of the fingerprint image capturing step, and the operations performed by the preprocessing units 132 and 221 and the feature point extraction units 134 and 222 are the operations of the feature point extraction step. Operations performed by the similarity determination processing unit 140 are operations performed by the connection information generation units 136 and 223 and operations performed by the feature pattern extraction units 138 and 224 are operations performed by the feature pattern extraction step. Corresponds to the operation of the search step.

  The fingerprint collation apparatus of this embodiment has such a configuration, and the operation will be described next. FIG. 6 is a flowchart showing an operation procedure for searching for a registered fingerprint image in the fingerprint collation processing unit 130. First, when the preprocessing unit 132 acquires the collation fingerprint image input from the fingerprint image input unit 110 (step 100), the preprocessing unit 132 performs preprocessing such as thinning (step 101). Next, the feature point extraction unit 134 extracts branch points and end points included in the collated fingerprint image after the preprocessing is completed as feature points (step 102). Based on the extracted feature points, the link information generation unit 136 generates the link table (excluding the feature patterns indicated by the functions 1 to 3) shown in FIG. 3 (step 103). Further, the feature pattern extraction unit 138 extracts a feature pattern corresponding to each branch point using the connection table (step 104).

  When the feature pattern of the collation fingerprint image is extracted in this way, the similarity determination processing unit 140 reads the feature pattern of one registered fingerprint image from the fingerprint DB 120 (step 105), and these two images (collation fingerprint image) And the registered fingerprint image) are determined (step 106). Specifically, the similarity determination processing unit 140 performs matching processing using the first feature pattern corresponding to the collation fingerprint image and the second feature pattern corresponding to the registered fingerprint image, and the matching distance M and the correlation degree S is calculated using the following equation:

M = ‖f-g‖
S = <f, g> / (‖f‖ × ‖g‖)
Here, ‖ and ‖ indicate norms, and <•> indicates an inner product. Further, f is a vector whose component is the first feature pattern (three functions 1 to 3). g is a vector having the second feature pattern as a component.

  The matching distance M indicates the length of the difference vector between the two vectors f and g. Correlation S indicates a cosine value (cos θ) of an angle θ formed by two vectors f and g. When the first feature pattern corresponding to the collation fingerprint image and the second feature pattern corresponding to the registered fingerprint image are very close, the lengths and directions of the two vectors f and g are similar. The matching distance M is small and the correlation degree S is close to 1. Since there are two or more feature patterns (number of branches) used for similarity determination, the matching distance M and the correlation degree S are calculated using each feature pattern, and the calculation results may be summed up for all feature patterns. .

  By the way, the collation fingerprint image includes a plurality of branch points, and there are a plurality of feature patterns corresponding to the respective branch points. Similarly, a single registered fingerprint image also includes a plurality of branch points. There are a plurality of feature patterns corresponding to each branch point. Therefore, it is considered that how to select the two feature patterns and calculate the above-described matching distance M and correlation S greatly affects the result of similarity determination. Therefore, in the present embodiment, one feature pattern corresponding to the verification fingerprint image is selected, and a matching distance M (or correlation S) is calculated between each feature pattern included in the registered fingerprint image, and the matching distance M Is extracted, and the matching distance corresponding to this combination is stored. Next, another feature pattern corresponding to the verification fingerprint image is selected, and a matching distance M is calculated between each feature pattern included in the registered fingerprint image (a feature pattern in which the matching distance M is stored is excluded). Then, the combination having the smallest matching distance M is extracted, and the matching distance corresponding to this combination is stored. In this way, the matching distance M corresponding to each feature pattern included in the collation fingerprint image is obtained and stored, and finally all the stored matching distances M are summed. All the matching distances M (or correlations S) calculated in this way are summed to determine the similarity between the two images.

  Next, the similarity determination processing unit 140 determines whether there is another registered fingerprint image for which the similarity determination has not been completed (step 107). If another registered fingerprint image exists, an affirmative determination is made, and the processing from step 105 onward is repeated for the next registered fingerprint image. If no other registered fingerprint image exists, a negative determination is made in the determination in step 107, and then the collation result output processing unit 142 outputs the result of the similarity determination (step 108). The determination result is output, for example, by displaying the accompanying information corresponding to the registered fingerprint images in order in the order in which the degree of similarity is determined to be large (the order of the total value of the matching distance M is small). .

  As described above, the branch point and the end point included in the fingerprint ridge are the major features for specifying the fingerprint, and the fingerprint collation apparatus according to the present embodiment shows a combination of functions for connecting the branch point and the end point. Fingerprint matching is performed by using feature patterns. In particular, by using a feature pattern indicating such a combination of functions, it is possible to reduce the amount of information necessary for fingerprint collation and shorten the time required for collation processing.

  In addition, this function is a linear function. By using a combination of the slopes of the straight lines indicated by the linear function as a feature pattern, the information amount of the feature pattern can be further reduced, and the processing time can be further shortened. Become. In addition, by using a relative value for each branch point of interest as the slope of this straight line, it becomes possible to remove the influence of the orientation when capturing the collation fingerprint image, and the orientation of the captured collation fingerprint image Since the process for correcting the error becomes unnecessary, the process can be simplified.

  In addition, it is possible to easily search for similar registered fingerprint images by sequentially reading out the feature patterns of registered fingerprint images stored in advance and comparing them with the feature patterns of collated fingerprint images. Even if there are many fingerprint images, the processing is not complicated and the processing can be simplified. In addition, by using the database creation apparatus shown in FIG. 5, it is possible to appropriately add a registered fingerprint image to be verified.

  In addition, this invention is not limited to the said embodiment, A various deformation | transformation implementation is possible within the range of the summary of this invention. For example, the operations of the fingerprint collation processing unit 130 and the database creation unit 220 of the above-described embodiment may be performed by a computer including a CPU, a ROM, a RAM, and the like. In this case, a fingerprint collation program stored in a ROM, RAM, or other storage device (hard disk device or the like) (executes each step shown in FIG. 6, or each unit of the fingerprint collation processing unit 130 or the database creation unit 220). A program for realizing the function may be executed by the CPU.

  In the above-described embodiment, the branch points and end points included in the ridges of the fingerprint image are extracted as feature points. However, similar branch points and end points are also included in the valley lines between adjacent ridges. Therefore, these may be extracted as feature points to perform fingerprint collation.

It is a figure which shows the structure of the fingerprint collation apparatus of one Embodiment. It is a figure which shows the specific example of the feature point contained in a collation fingerprint image. It is a figure which shows the specific content of the connection table produced | generated as connection information. It is explanatory drawing of a feature pattern. It is a figure which shows the structure of the database preparation apparatus which extracts the feature pattern previously about a registered fingerprint image, and registers with respect to fingerprint DB. It is a flowchart which shows the operation | movement procedure which searches a registered fingerprint image in a fingerprint collation process part.

Explanation of symbols

110, 210 Fingerprint image input unit 120 Fingerprint DB (database)
130 Fingerprint verification processing unit 132, 221 Preprocessing unit 134, 222 Feature point extraction unit 136, 223 Connection information generation unit 138, 224 Feature pattern extraction unit 140 Similarity determination processing unit 142 Verification result output processing unit 150, 230 Operation unit 160 , 240 Display unit 220 Database creation unit 225 File creation processing unit

Claims (7)

Fingerprint image capturing means for capturing a verification fingerprint image to be verified;
Feature point extracting means for extracting branch points and end points included in ridges or valleys included in the collated fingerprint image captured by the fingerprint image capturing means as feature points;
Connection information generating means for generating connection information indicating a connection state between the branch point and the end point included in the continuous ridge or valley line;
Based on the connection information, pay attention to each of the branch points, and each of the other branch points or end points adjacent to the ridge line or valley line including the focused branch point and the focus point. A feature pattern extracting means for determining a function that connects the branch point and extracting a combination of functions corresponding to the focused branch point as a feature pattern;
Search means for searching for a registered fingerprint image similar to the verification fingerprint image or accompanying information corresponding to the registered fingerprint image based on the feature pattern extracted by the feature pattern extraction means;
A fingerprint collation apparatus comprising: In claim 1,
The fingerprint verification apparatus, wherein the function is a linear function, and the feature pattern is a combination of slopes of straight lines indicated by the linear function. In claim 2,
The fingerprint collation apparatus characterized in that the slope of the straight line has a relative value for each branch point of interest. In any one of Claims 1-3,
The feature pattern corresponding to each of a plurality of branch points included in the registered fingerprint image further comprises a feature pattern storage means stored for each of the plurality of registered fingerprint images,
The search means performs a search process by comparing a feature pattern corresponding to the collation fingerprint image and feature patterns corresponding to a plurality of the registered fingerprint images stored in the feature pattern storage means. A fingerprint verification device. In claim 4,
When the feature pattern corresponding to the registered fingerprint image is acquired using the fingerprint image capturing unit, the feature point extracting unit, the connection information generating unit, and the feature pattern extracting unit, the feature pattern is converted into the feature pattern. A fingerprint collation apparatus further comprising a feature pattern storage processing means for storing in the pattern storage means. A fingerprint image capturing step for capturing a verification fingerprint image to be verified;
A feature point extracting step of extracting branch points and end points included in ridges or valleys included in the collation fingerprint image captured in the fingerprint image capturing step as feature points;
A connection information generating step for generating connection information indicating a connection state between the branch point and the end point included in the continuous ridge or the valley;
Based on the connection information, pay attention to each of the branch points, and each of the other branch points or end points adjacent to the ridge or valley line including the focused branch point and the focus. A feature pattern extraction step for determining a function that connects the branch point and extracting a combination of functions corresponding to the focused branch point as a feature pattern;
A search step for searching for a registered fingerprint image similar to the verification fingerprint image or accompanying information corresponding to the registered fingerprint image based on the feature pattern extracted in the feature pattern extraction step;
A fingerprint collation method comprising: Computer
Feature point extracting means for extracting branch points and end points included in ridges or valleys included in the collated fingerprint image captured by the fingerprint image capturing means as feature points;
Connection information generating means for generating connection information indicating a connection state between the branch point and the end point included in the continuous ridge or valley line;
Based on the connection information, pay attention to each of the branch points, and each of the other branch points or end points adjacent to the ridge or valley line including the focused branch point and the focus. A feature pattern extracting means for determining a function that connects the branch point and extracting a combination of functions corresponding to the focused branch point as a feature pattern;
Search means for searching for a registered fingerprint image similar to the verification fingerprint image or accompanying information corresponding to the registered fingerprint image based on the feature pattern extracted by the feature pattern extraction means;
Fingerprint verification program that makes it work.

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