Biometric information registration apparatus and biometric information registration method

A sensor acquires the same type of biometric information from plural fingers in association with an ID. A processor generates feature data used for verification from the biometric information, and generates characteristic data used for calculation of similarity between the plural fingers from the biometric information. Next, the processor compares the characteristic data and calculates the similarity between the plural fingers. The processor determines whether the feature data is registrable based on the similarity, and a memory stores the feature data in association with the ID when the feature data is registrable.

CROSS-REFERENCE TO RELATED APPLICATION

This application is based upon and claims the benefit of priority of the prior Japanese Patent Application No. 2015-028023, filed on Feb. 16, 2015, the entire contents of which are incorporated herein by reference.

FIELD

The embodiments discussed herein relates to a biometric information registration apparatus and a biometric information registration method.

BACKGROUND

In the personal authentication using biometric authentication, it is important that biometric information of a registrant is correctly registered at the time of registration. Even if rigorous identification is performed through biometric authentication at the time of personal authentication, in the case that biometric information of another person is fraudulently registered at the time of registration, the person could impersonate the registrant.

There are various possible cases in fraudulent registration of biometric information conducted by another person such as a case in which all of registered biometric information is biometric information of another person, and a case in which a portion of registered biometric information is that of another person. The latter case is such that in an attendance management system as an example, biometric information of the right hand of a person A is registered as the registered biometric information for right hand and biometric information of the left hand of another person B is registered as the registered biometric information of left hand with the cooperation of the person A. In this case, the person B can record the clock in time on behalf of the person A even when the person A is absent.

Against such fraudulent registration, in situations in which a biometric authentication system is used in companies, it is often a case that with the participation of employees, identification of the employees is conducted in front of an operator such as a manager, and then registration of biometric information is performed. By performing registration while the operator sees the employees in person, it is possible to prevent fraudulent registration such that biometric information of plural persons are registered in association with one ID (identification information).

However, as biometric authentication systems installed in mobile terminals such as a laptop personal computer and a smartphone grow popular, an opportunity that the employees register biometric information without an operator has been increasing. For that reason, it is desirable to take measures to prevent fraudulent registration without an operator.

Regarding the fraudulent registration prevention, a biometric information registration apparatus that can prevent fraudulent registration of biometric information of a person other than a person who should be registered (see Patent Document 1 as an example). This biometric information registration apparatus acquires related information related to a biological part registered as biometric information, and based on the related information, the apparatus determines whether or not the acquisition of the biometric information is correctly conducted.

In addition, a dishonest registration preventive apparatus for automatically and surely determining intermixture of another person's image without resorting to human labor and beforehand preventing dishonest registration due to substitution has been known (see Patent Document 2 as an example). This dishonest registration preventive apparatus detects positions of a face of a person from plural images acquired by consecutively photographing the face with a camera and calculates a variation between a position at this time and a position at the last time for the detected face positions. The dishonest registration preventive apparatus determines the image at this time to be a registrable image when the variation does not amount to the threshold, and determines the image at this time to be an unregistrable image when the variation exceeds the threshold.

An entry/exit management apparatus capable of reliably preventing spoofing has also been known (see Patent Document 3 as an example). This entry/exit management apparatus requests reading of new registration palm feature data of both hands upon new registration, stops registration when it determines that the new registration palm feature data of one hand is identical with new registration palm feature data of another hand. In addition, when the entry/exit management apparatus determines that the new registration palm feature data of the one hand is not identical with the new registration palm feature data of the another hand, it verifies the new registration palm feature data of the one hand and of the another hand against registered palm feature data registered in the biological database. When the identical data of either of the both hands is not found in the biological database, the entry/exit management apparatus registers the new registration palm feature data together with personal authentication information.

A human body recognition device capable of correctly performing registration/collation/updating even when a human body is replaced in the middle of performing the registration/collation/updating and preventing malfunctions by the erroneous recognition of the human body has also been known (see Patent Document 4 as an example). This human body recognition device changes the information to be utilized for recognition and output contents, in the case of detecting the replacement of the human body to be an object while performing the registration processing or updating processing or collation processing of the biological body feature information.

A fingerprint pattern sorting device to automatically sort a fingerprint pattern has also been known (see Patent Document 5 as an example). An algorithm to measure a quality of fingerprint images has also been known (see Non-Patent Document 1 as an example).

SUMMARY

According to an aspect of the embodiments, a biometric information registration apparatus includes a biometric information sensor, a processor, and a memory.

The biometric information sensor acquires the same type of biometric information from plural fingers in association with one ID. The processor generates feature data used for verification from the biometric information, and generates characteristic data used for calculation of similarity between the plural fingers from the biometric information. Next, the processor compares the characteristic data and calculates the similarity between the plural fingers. The processor determines whether the feature data is registrable based on the similarity, and a memory stores the feature data in association with the ID when the feature data is registrable.

DESCRIPTION OF EMBODIMENTS

Details of the embodiments are explained below with reference to the drawings.

In the biometric information registering device in Patent Document 1, a space to implement a task of registering biometric information is limited by the use of a camera to obtain related information. For that reason, this biometric information registering device is considered to be unsuitable for mobile terminals.

The dishonest registration preventive apparatus in Patent Document 2 detects a position of a face from plural images acquired by consecutively photographing the face with a camera, and such an apparatus is considered to be unsuitable for a registration task that registers biometric information of different biological parts such as a left hand and a right hand. Particularly, in a case of fingerprint authentication, the use of a contact-type sensor is predominant in biometric information acquisition, and a finger is lifted off the contact-type sensor when switching fingers. Thus, it is difficult to implement this dishonest registration preventive apparatus.

The entry/exit management apparatus in Patent Document 3 performs verification by comparing palm feature data of both hands to be registered. However, this verification only verifies whether or not the palm feature data of the two hands is identical, but does not verify whether the palm feature data is of multiple persons. In addition, the apparatus implements a registration double check by comparing with the registered palm feature data. However, if palm feature data for multiple persons has not been registered, fraudulent registration is possible.

As described above, in the existing fraudulent registration prevention technology, it is difficult, without an operator, to effectively prevent fraudulent registration that registers feature data of multiple persons under a single ID in a biometric authentication system installed in a mobile terminal etc.

It is noted that such problems occur not only in a case of registering fingerprint information but also in a case of registering other biometric information such as finger vein images.

FIG. 1illustrates an example of a functional configuration of a biometric information registration apparatus. A biometric information registration apparatus101inFIG. 1includes a biometric information acquisition unit111, a feature data generation unit112, a characteristic data generation unit113, a similarity calculation unit114, a registration determination unit115, and a storage unit116.

FIG. 2is a flowchart illustrating an example of biometric information registration processing that is performed by the biometric information registration apparatus101inFIG. 1. First of all, the biometric information acquisition unit111acquires the same type of biometric information from plural fingers in association with an ID121(step201). Next, the feature data generation unit112generates feature data122to be used for verification from the biometric information (step202), and the characteristic data generation unit113generates characteristic data to be used for calculation of similarity between the plural fingers from the biometric information (step203).

Next, the similarity calculation unit114compares the characteristic data and calculates the similarity between the plural fingers (step204). The registration determination unit115determines whether or not the feature data122is registrable based on the similarity (step205), and registers the feature data122in the storage unit116in association with the ID121when the feature data122is registrable (step206).

According to this biometric information registration apparatus101, fraudulent registration of biometric information can be prevented with a simple method.

Next, biometric information registration processing when fingerprint information is used as biometric information of fingers is explained. The biometric information acquisition unit111that acquires fingerprint information is realized by a fingerprint sensor such as a capacitive fingerprint sensor, a thermal fingerprint sensor, an electric field fingerprint sensor, an optical fingerprint sensor, and an ultrasonic fingerprint sensor, captures fingerprint images from the fingers presented by a registrant, and converts the captured fingerprint images into digital images. It is possible to capture the fingerprint images sequentially one finger after another by a single fingerprint sensor, or it is also possible to capture a fingerprint image of plural fingers at once by a fingerprint sensor that has a wide capture area and can capture plural fingerprints at the same time. The fingerprint sensor may be connected to the biometric information registration apparatus101via an interface or may be built into the biometric information registration apparatus101.

FIG. 3is a flowchart illustrating an example of biometric information registration processing by using fingerprint information. In this biometric information registration processing, a prescribed number of fingers of one hand or both hands of a registrant are a registration target, and the fingerprint information of these fingers will be registered in the storage unit116. The registration target may be all fingers of both hands of the registrant.

First, the biometric information acquisition unit111captures a fingerprint image from one finger of a hand of the registrant (step301). Next, from the fingerprint image, the feature data generation unit112generates feature data122(step302) that is used for verification at the time of biometric authentication. For the feature data122, a position of a feature point included in the fingerprint image can be used as an example, and as the feature point, for example, minutia such as an ending point at which a ridge terminates or a bifurcation point at which a ridge splits into two can be used.

Next, the characteristic data generation unit113generates characteristic data that is used to calculate similarity between plural fingers from fingerprint images (step303). For the characteristic data, it is desirable that data that is similar between different fingers of one person be used. The feature data122such as minutia is not suitable for the characteristic data because the feature data122is not similar between different fingers of a person.

For the characteristic data that is similar between different fingers of a person, as an example, a characteristic value such as the size (width or area etc.) of an area that includes a fingerprint (fingerprint area) in a fingerprint image, the fingerprint pattern, the quality of the fingerprint image, the width of ridges, and the distance between ridges can be used. The characteristic data generation unit113can generate the characteristic data by combining plural types of characteristic values.

The characteristic data generation unit113can obtain the width of a fingerprint area by detecting the leftmost black pixel and the rightmost black pixel of black pixels that indicate ridges in a fingerprint image and by calculating the distance between these two black pixels.

For the fingerprint pattern, as disclosed in Patent Document 5 as an example, plural types of patterns have been known, and the fingerprint patterns of a fingerprint image can be represented by using values indicating the likelihood corresponding to each of the patterns. When three types of patterns including the whorl, loop, and arch are used as an example, the values representing these fingerprint patterns are vector values such as (P1, P2, P3). Each of P1, P2, and P3 represents the likelihood of being whorl, the likelihood of being loop, and the likelihood of being arch, respectively.

The characteristic data generation unit113can calculate the quality of a fingerprint image based on the contrast etc. of the fingerprint image by using an algorithm disclosed in Non-Patent Document 1 as an example.

FIG. 4illustrates an example of a method of calculating the width of a ridge. The characteristic data generation unit113detects the center of a whorl in a fingerprint from a fingerprint image, sets the detected position to be a starting point, and searches for a black pixel in each of the leftward direction (180°), the upward direction (90°), and the rightward direction (0°) until the end of the image.

The characteristic data generation unit113, then, detects the number of consecutive black pixels from each of plural black pixel concatenated areas, and calculates a statistical value of the detected number of black pixels as the width of the ridge. For the statistical value of the number of black pixels, the average value, the median value, the maximum value, and the minimum value can be used as an example. For example, in a case of a black pixel concatenated area501inFIG. 5, because there are four consecutive black pixels in the rightward direction, the number of black pixels in the rightward direction is four.

The characteristic data generation unit113can obtain a distance between ridges based on the search result from the center of the whorl to the end of the image. For example, the characteristic data generation unit113obtains the distance between ridges by taking a black pixel concatenated area including consecutive black pixels as a single ridge, detecting the number of ridges existing between the center and the end of the image, and dividing the number of pixels (searched distance) in a searched direction by the number of ridges.

Next, the similarity calculation unit114checks whether or not registration of a fingerprint image of any finger has been approved (step304). When the fingerprint image captured in step301is a fingerprint image of the first finger of the registration target, there has not yet been a finger approved for registration of its fingerprint image (step304, No). In this case, the registration determination unit115approves the registration of the fingerprint image of the first finger and checks whether or not fingerprint images of all the fingers of the registration target have been captured (step307). When a fingerprint image of any of the fingers has not been captured (step307, No), the biometric information registration apparatus101repeats the processing in step301and subsequent steps for another finger.

Meanwhile, when the fingerprint image captured in step301is a fingerprint image of the second finger or a subsequent finger of the registration target, there is a finger approved for registration of its fingerprint image (step304, Yes). In this case, the similarity calculation unit114calculates an index of similarity between the characteristic data of the fingerprint image of the finger that is approved for registration and the characteristic data generated in step303(step305).

For the index of similarity, the degree of similarity that indicates that the two pieces of characteristic data are more similar as the value becomes greater, or the degree of difference that indicates that the two pieces of characteristic data are more similar as the value becomes smaller can be used.

Here, the characteristic data of the fingerprint image of a finger approved for registration is represented by an n-dimensional vector X having n characteristic values xi (i=1˜n) as elements, and the characteristic data generated in step303is represented by an n-dimensional vector Y having n characteristic values yi (i=1˜n).
X=(x1, x2, . . . ,xn)  (1)
Y=(y1,y2, . . . ,yn)  (2)

At that time, a similarity S between vector X and vector Y can be calculated from the following equation as an example.
S=#{|xi−yi|<THi}, i=1, . . . ,n(3)

THi on the right-hand side of the equation (3) represents a threshold for the i-th characteristic value, and #{|xi−yi|<THi} represents the number of characteristic values that satisfy a condition such that the absolute value of the difference between xi and yi is less than THi. Consequently, the similarity S is an integer not less than 0 and not more than n. Cosine similarity between vector X and vector Y can also be used as the similarity S.

In addition, for the degree of difference D between vector X and vector Y, distance values such as L1-norm D1, L2-norm D2 can be used.
D1=Σ|xi−yi|(4)
D2=Σ(xi−yi)2(5)

Σ on the right-hand side of the equation (4) and the equation (5) represents the sum for i=1˜n.

Next, the registration determination unit115determines whether or not the feature data122generated in step302can be registered in accordance with the calculated similarity (step306). When the similarity to the characteristic data of all the fingers that have been approved for registration satisfies the determination condition, the registration determination unit115approves registration of the feature data122. On the other hand, when the similarity to the characteristic data of any of the fingers that have been approved for registration does not satisfy the determination condition, the registration determination unit115does not approve the registration of the feature data122.

When the degree of similarity is used as an index of similarity, the registration determination unit115can use a determination condition wherein the degree of similarity is greater than a prescribed threshold. In this case, the registration determination unit115compares the degree of similarity with the threshold. When the degree of similarity is greater than the threshold, the determination condition is satisfied, and when the degree of similarity is equal to or less than the threshold, the determination condition is not satisfied.

Moreover, when the degree of difference is used as an index of similarity, the registration determination unit115can use a determination condition wherein the degree of difference is smaller than a prescribed threshold. In this case, the registration determination unit115compares the degree of difference with the threshold. When the degree of difference is smaller than the threshold, the determination condition is satisfied, and when the degree of difference is equal to or greater than the threshold, the determination condition is not satisfied.

In this manner, as the vector X and the vector Y become more similar to each other, the determination condition is more likely to be satisfied, and the feature data122is more likely to be approved for registration. On the other hand, as the vector X and the vector Y become more different, the determination condition is less likely to be satisfied, and the feature data122is less likely to be approved for registration.

When registration is approved (step306, Yes), the registration determination unit115checks whether or not fingerprint images of all fingers of the registration target have been captured (step307). When no fingerprint image has been captured for any finger (step307, No), the biometric information registration apparatus101repeats the processing in step301and subsequent steps for another finger.

When the fingerprint images of all fingers of the registration target have been captured (step307, Yes), the registration determination unit115registers the feature data122and the characteristic data of the fingers in the storage unit116in association with the ID121(step308). As a result, fingerprint images of all fingers of a registration target are determined to be the fingerprint images of one person and are registered in association with the ID121.

On the other hand, when registration is not approved (step306, No), the registration determination unit115discards the feature data112and the characteristic data of all fingers that have been generated so far (step309). As a result, a fingerprint image of at least one finger of a registration target is determined to be the fingerprint image of another person, and registration of fingerprint images of all fingers is rejected.

FIG. 6illustrates an example of the feature data and the characteristic data registered in the storage unit116. The storage unit116stores the feature data122and the characteristic data601in association with the ID121. For each of the fingers of the registration target, the feature data122and the characteristic data601are registered in association with the ID121.

The biometric information registration apparatus101performs biometric authentication processing by using the feature data122registered in the storage unit116. In the biometric authentication processing, the biometric information acquisition unit111acquires a fingerprint image from at least one finger of a hand of a person being authenticated, the feature data generation unit112generates feature data from the fingerprint image for each of the fingers. Afterwards, the biometric information registration apparatus101verifies the generated feature data for each of the fingers by checking it against the feature data122for each of the fingers registered in the storage unit116, and determines whether or not the person being authenticated is a registered person corresponding to the ID121based on the verification result.

According to the biometric information registration processing inFIG. 3, aside from feature data for verification, characteristic data for calculating similarity is generated from a fingerprint image of each finger, and similarity is calculated by comparing the generated characteristic data with characteristic data of each finger registered under a single ID. As a result of determining whether or not the feature data can be registered in accordance with the calculated similarity, it is possible to prevent fraudulent registration that registers feature data of multiple persons under a single ID. In addition, by using plural types of characteristic values that can be extracted from a fingerprint image as the characteristic data, it is possible to improve the accuracy of the determination result of whether or not the feature data can be registered.

In the meantime, additional registration or reregistration of fingerprint images is sometime performed after the feature data122and the characteristic data601of the fingers of the registration target are registered in the storage unit116. The additional registration is processing to add the feature data and the characteristic data of a new finger that has not been included in the registration target, and the reregistration is processing to overwrite the feature data and the characteristic data of the registered fingers.

FIG. 7illustrates an example of biometric information registration processing performed at the time of additional registration or reregistration. The fingers of the registration target in the additional registration or the reregistration can be one finger or plural fingers.

First, the similarity calculation unit114acquires the characteristic data601of all fingers registered in the storage unit116in association of the ID121(step701). Next, the biometric information acquisition unit111acquires a fingerprint image from one finger of a registration target of additional registration or reregistration (step702). Processing in the next steps703and704is the same as the processing in steps302and303inFIG. 3.

Next, the similarity calculation unit114calculates an index of similarity between the characteristic data601of each finger acquired from the storage unit116and the characteristic data generated in step704(step705). The registration determination unit115determines whether or not the feature data generated in step703can be registered in accordance with the calculated similarity (step706). When the similarity to the characteristic data601of all the fingers acquired from the storage unit116satisfies the determination condition that is similar to the condition in step306, the registration determination unit115approves registration of the feature data. On the other hand, when the similarity to the characteristic data of any of the fingers acquired from the storage unit116does not satisfy the determination condition, the registration determination unit115does not approve the registration of the feature data.

When registration is approved (step706, Yes), the registration determination unit115checks whether or not fingerprint images of all fingers of the registration target of additional registration or reregistration have been captured (step707). When no fingerprint image has been captured for any finger (step707, No), the biometric information registration apparatus101repeats the processing in step702and subsequent steps for another finger.

When the fingerprint images of all fingers of the registration target have been captured (step707, Yes), the registration determination unit115registers the feature data and the characteristic data of the fingers in the storage unit116in association with the ID121(step708). In the case of additional registration, the feature data and the characteristic data of a finger of the registration target is newly registered, and in the case of reregistration, the feature data122and the characteristic data601of the registered finger are overwritten. On the other hand, when registration is not approved (step706, No), the registration determination unit115discards the feature data and the characteristic data of all fingers that have been generated so far (step709).

According to the biometric information registration processing inFIG. 7, it is possible to prevent fraudulent registration that registers feature data of a different person under a registered ID at the time of additional registration or reregistration.

A time period from registration of the feature data122and the characteristic data601in the storage unit116through the biometric information registration processing inFIG. 3to the additional registration or reregistration inFIG. 7can be a short period of time of two or three days or it can be a long period of time of one month or longer.

For example, when additional registration or reregistration is performed after the changing of seasons, the characteristic value may vary in the same person due to the drying or moistening effect, and it is possible in such a case that registration is not approved. Considering this, it is effective to change the similarity calculation method based on the characteristic data in accordance with the changing of seasons. An example of the characteristic value that is subject to effects of the changing of seasons is the quality of fingerprint images.

In this case, the storage unit116stores a generation date on which the characteristic data601is generated in association with the characteristic date601. The similarity calculation unit114changes the similarity calculation method based on the generation date stored in the storage unit116and the generation date of the characteristic date generated from fingerprint images at the time of additional registration or reregistration.

When the difference between the two generation dates is greater than a prescribed threshold, the similarity calculation unit114may exclude the quality of fingerprint images and calculate similarity, or may reduce the weight of the quality of fingerprint images and calculate similarity. A time period of a half year may be an example of the prescribed threshold.

In addition, when one of the two generation dates is winter (December to February), the similarity calculation unit114may exclude the quality of fingerprint images and calculate similarity, or may reduce the weight of the quality of fingerprint images and calculate similarity.

This alteration of the characteristic value used for calculation of similarity based on the generation date of the characteristic data decreases the likelihood of erroneously determining the same person to be a difference person due to the changing of seasons. Instead of the generation date of the characteristic date, generation date and time of the characteristic data can be also used.

The configuration of the biometric information registration apparatus101illustrated inFIG. 1is only an example, and some of the elements in the configuration may be omitted or changed in accordance with the usage or conditions of the biometric information registration apparatus101.

The flowcharts inFIG. 2,FIG. 3andFIG. 7are also mere examples, and a portion of the processing may be omitted or changed in accordance with the configuration or conditions of the biometric information registration apparatus101. For example, the processing in step202and the processing in step203inFIG. 2can be in reverse order. Similarly, the processing in step302and the processing in step303FIG. 3can be in reverse order, and the processing in step703and the processing in step704inFIG. 7can be in reverse order.

In the biometric information registration processing inFIG. 3andFIG. 7, instead of capturing the fingerprint images one finger after another and determining whether or not feature data can be registered, a fingerprint image of plural fingers may be captured at once and whether or not feature data can be registered may be determined at once. In this case, the processing in step307inFIG. 3and the processing in step707inFIG. 7can be omitted.

Instep306inFIG. 3, the registration determination unit115may determine whether or not the feature data122can be registered in accordance with similarity to the characteristic data of any one finger of the fingers that are approved for registration. In this case, when similarity to the characteristic data of one finger satisfies the determination condition, the registration determination unit115approves registration of the feature data122.

Instep706inFIG. 7, the registration determination unit115may determine whether or not the feature data can be registered in accordance with similarity to the characteristic data601of any one finger from among the characteristic data601of the fingers stored in the storage unit116. In this case, when similarity to the characteristic data601of one finger satisfies the determination condition, the registration determination unit115approves registration of the feature data.

In the biometric information registration processing inFIG. 3andFIG. 7, instead of the degree of similarity in equation (3), the degree of difference in equation (4), and the degree of difference in equation (5), other degrees of similarity or other degrees of difference can be used. Characteristic values other than the size of the fingerprint area in a fingerprint image, the fingerprint pattern, the quality of fingerprint images, the width of ridges, and the distance between ridges can be used as characteristic data. Instead of fingerprint images, other biometric information such as finger vein images can be used to generate feature data and characteristic data.

The biometric information registration apparatus101inFIG. 1can be realized by using an information processing apparatus (computer) illustrated inFIG. 8as an example.

The information processing apparatus inFIG. 8has a Central Processing Unit (CPU)801, a memory802, an input device803, an output device804, an auxiliary storage device805, a media drive device806, and a network connection device807. These elements are connected to each other via a bus808. The biometric information acquisition unit111inFIG. 1may be connected to the bus808.

The memory802is, for example, a semiconductor memory such as a Read Only Memory (ROM), a Random Access Memory (RAM), and a flash memory, and stores a program and data used in the biometric information registration processing. The memory802can be used as the storage unit116inFIG. 1.

By executing the program with the use of the memory802, for example, the CPU801(processor) operates as the feature data generation unit112, the characteristic data generation unit113, the similarity calculation unit114, and the registration determination unit115inFIG. 1.

The input device803is a keyboard or a pointing device as an example, and is used for input of instructions and information from an operator or a user. The output device804is a display device, a printer, or a speaker as an example, and is used for output of inquiries or instructions and processing results to the operator or the user. The processing results include information indicating completion of registration of biometric information or rejection of registration.

Examples of the auxiliary storage device805are a magnetic disk device, an optical disk, a magnetic optical disk device, and a tape device. The auxiliary storage device805may be a hard disk drive. The information processing apparatus can store a program and data in the auxiliary storage device805and load them into the memory802to use them. The auxiliary storage device805can be used as the storage unit116inFIG. 1.

The media drive device806drives a portable recording medium809and accesses the recorded contents. The portable recording medium809are a memory device, a flexible disk, an optical disk, a magnetic optical disk and the like. The portable recording medium809may be a Compact Disk Read Only Memory (CD-ROM), a Digital Versatile Disk (DVD), a Universal Serial Bus (USB), etc. An operator can store a program and data in this portable recording medium809and load them into the memory802to use them.

As described above, a computer-readable recording medium that stores programs and data used in the biometric information registration processing is a physical (non-transitory) recording medium.

The network connection device807is a communication interface that is connected to a communication network such as a Local Area Network, and a Wide Area Network, and performs data conversion that is associated with communication. The information processing apparatus can receive a program and data from external apparatuses via the network connection device807and use the program and data by loading them into the memory802.

The information processing apparatus can receive a processing request from a user terminal via the network connection device807, perform the biometric information registration processing, and transmit a processing result to the user terminal.

It is noted that the information processing apparatus does not need to include all of the elements, but some of the elements can be omitted in accordance with the usage or conditions. For example, the input device803can be omitted when there is no instruction or information that need to be input from an operator or a user. The output device804can be omitted when there is no inquiry or information and a processing result that need to be output to the operator or the user.

Moreover, when there is no need to communicate with other apparatuses, the network connection device807can be omitted, or when the portable recording medium809is not used, the media drive device806may be omitted.