WO2011062096A1 - Multimodal authentication device - Google Patents

Multimodal authentication device Download PDF

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Publication number
WO2011062096A1
WO2011062096A1 PCT/JP2010/069990 JP2010069990W WO2011062096A1 WO 2011062096 A1 WO2011062096 A1 WO 2011062096A1 JP 2010069990 W JP2010069990 W JP 2010069990W WO 2011062096 A1 WO2011062096 A1 WO 2011062096A1
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Prior art keywords
collation
verification
matching
user
authentication
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PCT/JP2010/069990
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French (fr)
Japanese (ja)
Inventor
中村　陽一
亀井　俊男
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日本電気株式会社
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Publication of WO2011062096A1 publication Critical patent/WO2011062096A1/en

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
    • G06F21/30—Authentication, i.e. establishing the identity or authorisation of security principals
    • G06F21/31—User authentication
    • G06F21/32—User authentication using biometric data, e.g. fingerprints, iris scans or voiceprints
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/25—Fusion techniques
    • G06F18/254—Fusion techniques of classification results, e.g. of results related to same input data
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
    • G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
    • G06V40/12—Fingerprints or palmprints
    • G06V40/13—Sensors therefor
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
    • G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
    • G06V40/14—Vascular patterns
    • G06V40/145—Sensors therefor
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L9/00—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols
    • H04L9/32—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols including means for verifying the identity or authority of a user of the system or for message authentication, e.g. authorization, entity authentication, data integrity or data verification, non-repudiation, key authentication or verification of credentials
    • H04L9/3226—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols including means for verifying the identity or authority of a user of the system or for message authentication, e.g. authorization, entity authentication, data integrity or data verification, non-repudiation, key authentication or verification of credentials using a predetermined code, e.g. password, passphrase or PIN
    • H04L9/3231—Biological data, e.g. fingerprint, voice or retina
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
    • G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
    • G06V40/12—Fingerprints or palmprints
    • G06V40/1341—Sensing with light passing through the finger

Definitions

  • the present invention relates to a multimodal authentication technique using a plurality of physical features.
  • the present invention has been made in view of the above-described circumstances, and provides a multimodal authentication apparatus capable of improving both safety and convenience in personal authentication using two or more types of physical features.
  • the purpose is to provide.
  • the multimodal authentication apparatus applies a plurality of types of matching algorithms to the first physical characteristics of the input authentication target person to determine whether or not the authentication target person belongs to a legitimate user.
  • a second verification unit that applies one or more verification algorithms to determine whether or not the second physical feature of the input person to be authenticated is a regular user;
  • collation is established in the collation using at least one of the collation algorithms, it is determined that the first physical feature of the input user is that of the regular user.
  • the multimodal authentication apparatus applies a plurality of types of verification algorithms to determine whether or not the first physical feature of the input authentication target person belongs to the authorized user.
  • a second verification unit that determines whether or not the input second physical feature of the person to be authenticated is an authorized user by applying one or more verification algorithms.
  • an authentication means for determining that the person to be authenticated is a regular user when the first and second matching means are matched, wherein the first matching means includes the plurality of types of matching.
  • the multimodal authentication method is a collation for determining whether or not the first physical feature of the input authentication target person belongs to a regular user by applying a plurality of types of collation algorithms.
  • a first physical feature of the user that is input when the collation is established in the collation using at least one of the plural collation algorithms among the plurality of collation algorithms A first collation step for judging that the second physical feature of the person to be authenticated is applied and one or more collation algorithms are applied to determine whether or not the legitimate user belongs.
  • verification is established in the second verification step to be performed and the first and second verification steps, it is determined that the person to be authenticated is a regular user. Characterized in that it comprises a testimony step.
  • FIG. 1 is a diagram illustrating a configuration of a multimodal authentication device 100 according to the present embodiment.
  • the multimodal authentication device 100 is a device that performs authentication by combining a plurality of physical features (modalities).
  • fingerprints and finger veins are used as a plurality of modalities.
  • a feature shape feature representing a human body shape such as a fingerprint, a face image, and an iris may be used.
  • the combination of physical features of fingerprints and finger veins and the combination of physical features of faces and iris are obtained from the same physical part (finger or face).
  • the multimodal authentication device 100 includes an upper housing 10a, a lower housing 10b, a first light source 30a provided in the upper housing 10a, and a first light source 30a provided in the lower housing 10b. 2 light sources 30 b, an imaging device (input means) 40, and a computer 50.
  • two types of collation methods are prepared for each physical feature of the finger and the finger vein. When the collation is established by any one of the collation methods, it is determined that this physical feature is the physical feature of the person (details will be described later).
  • functions of the computer 50 serving as the center of the multimodal authentication device 100 will be described.
  • FIG. 2 is a functional block diagram of the computer 50.
  • the computer 50 includes a fingerprint collation unit 510a, a fingerprint collation database 520a, a finger vein collation unit 510b, a finger vein collation database 520b, and a personal authentication unit 530.
  • the fingerprint collation unit 510a determines whether or not the user's fingerprint corresponding to the fingerprint image output from the imaging device 40 is that of the user.
  • the fingerprint collation unit 510a includes a plurality of types of fingerprint collation algorithms.
  • the fingerprint verification unit 510a includes a first fingerprint verification module MF1 for verifying a user's fingerprint by an image pattern matching method and a second fingerprint verification module for verifying a user's fingerprint by a minutia method. MF2.
  • a first fingerprint verification template TF1 for the first fingerprint verification module and a second fingerprint verification template TF2 for the second fingerprint verification module are registered.
  • a line image corresponding to the fingerprint of the authorized user (here, the principal) and minutia information of the principal's fingerprint are registered. Yes.
  • a unique user ID may be assigned to each regular user, and a line image may be registered in association with the user ID (this is the same for other templates described later).
  • the finger vein collating means 510b determines whether or not the user's blood vessel pattern (vein pattern) corresponding to the finger vein image output from the imaging device 40 is that of the user.
  • the finger vein matching unit 510b includes a plurality of types of finger vein matching algorithms.
  • the finger vein matching unit 510b includes a first finger vein matching module for matching the user's finger vein by the pattern matching method and a second finger vein for matching the user's finger vein by the feature amount method.
  • a finger vein verification module is a first finger vein matching module for matching the user's finger vein by the pattern matching method and a second finger vein for matching the user's finger vein by the feature amount method.
  • a first finger vein matching template TV1 for the first finger vein matching module and a second finger vein matching template TV2 for the second finger vein matching module are registered. Yes.
  • an image representing the blood vessel pattern of the person and the feature amount of the blood vessel pattern of the person are registered.
  • the personal authentication unit 530 receives the verification result of the fingerprint verification unit 510a and the verification result of the finger vein verification unit 510b, and performs personal authentication. Specifically, the personal authentication unit 530 performs AND type integration of the fingerprint matching result and the blood vessel pattern matching result (see ⁇ in FIG. 5), and when both fingerprint matching and vein matching are established. Only when the person to be authenticated is determined to be the person.
  • features of fingerprint matching and finger vein matching according to the present embodiment will be described.
  • FIG. 3A is a diagram illustrating the principle of reflected light sensing realized by the multimodal authentication device 100.
  • the multimodal authentication device 100 performs reflected light sensing with the second light source 30b and the imaging device 40 provided in the lower housing 10b, and obtains a fingerprint image as shown in FIG. 4A. Specifically, a fingerprint image in which the ridge RL where the skin is raised is bright and the valley line VL in between is dark (see FIG. 4A).
  • the matching algorithm of the image pattern matching method extracts a ridge pattern as a line image by performing image processing such as binarization on the fingerprint image obtained by the imaging device 40, and performs matching using the extracted line image. It is an algorithm to do.
  • the image pattern matching method uses an image corresponding to the fingerprint of the person registered in the first fingerprint matching template TF1 and a line obtained by the first fingerprint matching module MF1 at the time of matching. By directly comparing the image and calculating the similarity, it is determined whether or not it is the fingerprint of the user.
  • the matching algorithm of the minutia method is an algorithm that extracts minutiae (feature points) from the fingerprint image obtained by the imaging device 40 and collates using minutiae information such as the position, type, and direction of the minutiae.
  • the minutia method is also well known in the art, the minutia information corresponding to the fingerprint of the person registered in the second fingerprint collation template TF2, and the minutiae obtained by the second fingerprint collation module MF2 at the time of collation. By comparing the information, it is determined whether or not it is the fingerprint of the person.
  • two types of fingerprint matching methods are OR-integrated (see ⁇ in FIG. 5), and matching is established by any one of the fingerprint matching methods. Then, it is determined that the fingerprint is the person's fingerprint (first physical characteristic).
  • FIG. 3B is a diagram illustrating the principle of transmitted light sensing realized by the multimodal authentication device 100.
  • the multimodal authentication device 100 performs transmitted light sensing using the first light source 30a and the imaging device 40 provided in the upper housing 10a, and obtains a finger vein image as shown in FIG. 4B. Specifically, a finger vein image in which the blood vessel portion BA is dark and the other portions are bright is obtained by absorbing near-infrared light by hemoglobin in the blood (see FIG. 4B).
  • the authentication algorithm of the image pattern matching method is an algorithm for extracting a blood vessel pattern by performing image processing on the finger vein image obtained by the imaging device 40 and collating an image representing the extracted blood vessel pattern.
  • the image pattern matching method includes an image representing the blood vessel pattern of the person (user) registered in the first finger vein matching template TV1 and the first finger vein matching module at the time of matching. By directly comparing the line image obtained by the MV1, it is determined whether or not the blood vessel pattern (vein pattern) of the user.
  • the collation algorithm of the feature amount method performs image processing on the finger vein image obtained by the imaging device 40, thereby thinning the blood vessel portion and then sequentially connecting the lines between the branch points from the branch points to the branch points.
  • feature quantities such as branch point coordinates, length, branch angle at the branch point, etc. are extracted, and the extracted feature quantities are collated.
  • the feature amount method is also obtained by the second finger vein matching module MV2 at the time of matching with the feature amount of the person's blood vessel pattern registered in the second finger vein matching template TV2. It is determined whether or not the blood vessel pattern (vein pattern) of the person is by comparing the characteristic amount of the blood vessel pattern to be obtained.
  • the two types of finger vein matching methods described above are also integrated by OR type integration ( ⁇ in FIG. If the collation is established by any one of the finger vein collation methods, it is determined that the blood vessel pattern (vein pattern; second physical feature) of the person.
  • the fingerprint matching result and the blood vessel pattern matching result are AND-type integrated (see ⁇ in FIG. 5), and only when it is determined that the person is the person in both fingerprint matching and vein matching. It is determined that the user (authenticated person) who acquired the image and the finger vein image is the person himself / herself.
  • Embodiment 1 Operation of Embodiment A user who is an authentication target puts a finger between the upper housing 10a and the lower housing 10b of the multimodal authentication device 100, and the belly of the finger is placed on the template TE of the lower housing 10b. Place (see FIG. 1).
  • the multimodal authentication device 100 detects that the user's finger belly is placed on the template TE, the multimodal authentication device 100 performs reflected light sensing using the second light source 30b and the imaging device 40 provided in the lower housing 10b.
  • a fingerprint image as shown in 3A is acquired.
  • transmitted light sensing is performed by the first light source 30a and the imaging device 40 provided in the upper housing 10a, and a finger vein image as shown in FIG. 3B is acquired.
  • the imaging device 40 transmits the acquired fingerprint image and finger vein image to the computer 50.
  • an image is acquired by bringing a finger into contact with the sensor surface (template TE) (when a contact sensor is used), but the sensor is a non-contact sensor (that is, a non-contact sensor). ).
  • the template TE is not necessary.
  • a method for determining whether or not the finger is present at a predetermined position when there is no template TE for example, a method in which images obtained successively are arranged in time series and compared can be employed.
  • FIG. 6 is a flowchart showing fingerprint collation processing using the multimodal authentication device 100.
  • the fingerprint verification unit 510a of the computer 50 receives the fingerprint image of the user from the imaging device 40 (step S1a), the fingerprint output from the imaging device 40 using the first fingerprint verification module (image pattern matching method) MF1. It is determined (collated) whether or not the user's fingerprint corresponding to the image is that of the user (step S2a).
  • the fingerprint collation unit 510a determines that the fingerprint of the user who is the person to be authenticated is the fingerprint of the user (ie, collation is established) by fingerprint collation using the first fingerprint collation module MF1 (step S3a; YES)
  • the process proceeds to step S6a without performing collation using the second fingerprint collation module (maneuver method) MF2.
  • the collation using the second fingerprint collation module MF2 is not performed as follows.
  • the collation using the first fingerprint collation module MF1 is performed in order to determine that the user's fingerprint is the original person (see FIG. 5 ⁇ ). This is because there is no need for further verification if the above holds. By adopting such a configuration, the verification speed can be improved and the processing can be simplified.
  • step S3a when collation using the first fingerprint collation module MF1 is not established (step S3a; NO), the fingerprint image output from the imaging device 40 using the second fingerprint collation module (maneuver method) MF2 is used. It is judged (verified) whether or not the user's fingerprint corresponding to is the person's own (step S4a).
  • the fingerprint collation unit 510a determines that the fingerprint of the user who is the person to be authenticated is the fingerprint of the user (that is, collation is established) by fingerprint collation using the second fingerprint collation module MF2 (step S5a; YES)
  • step S5a the personal authentication means 530 is notified that the verification has been established (step S6a), and the process is terminated.
  • step S5a when the collation using the second fingerprint collation module is not established (step S5a; NO), the fingerprint collation means 510a notifies the personal authentication means 530 that the collation is not established (step S7a). The process is terminated.
  • FIG. 7 is a flowchart showing finger vein collation processing using the multimodal authentication device 100.
  • the finger vein matching unit 510b of the computer 50 When the finger vein collating unit 510b of the computer 50 receives the finger vein image of the user from the imaging device 40 (step S1b), the finger vein matching unit 510b outputs the image from the imaging device 40 using the first finger vein matching module (image pattern matching method) MV1. It is determined (collated) whether or not the user's blood vessel pattern (vein pattern) corresponding to the finger vein image to be processed is the user's own (step S2b).
  • the process proceeds to step S6b without performing collation using the second finger vein collation module (feature quantity method) MV2.
  • the reason why collation using the second finger vein collation module MV2 is not performed is the same as in the case of the fingerprint collation described above.
  • the collation is established by the finger vein collation method, the user's blood vessel pattern is determined to be the person's own (see FIG. 5 ⁇ ), so that the collation using the first finger vein collation module MV1 is established. This is because there is no need for further verification.
  • the second finger vein collation module (feature amount method) MV2 is used and output from the imaging device 40. It is determined (collated) whether or not the user's blood vessel pattern (vein pattern) corresponding to the finger vein image is that of the user (step S4b).
  • the finger vein matching unit 510b determines that the blood vessel pattern of the user who is the person to be authenticated is the blood vessel pattern of the user by the vein matching using the second finger vein matching module MV2 (that is, the matching is established) (step S1).
  • step S6b the personal authentication means 530 is notified that the verification has been established (step S6b), and the process is terminated.
  • step S6b the verification using the second finger vein verification module MV2
  • step S7b the finger vein verification unit 510b notifies the personal authentication unit 530 that the verification has not been established ( Step S7b), the process is terminated.
  • the personal authentication unit 530 AND-integrates the fingerprint verification result received from the fingerprint verification unit 510a and the finger vein verification result received from the finger vein verification unit 510b (see [gamma] in FIG. 5). Only when both of the above verification and finger vein verification are established, the user who is the person to be authenticated is determined to be the person himself / herself.
  • the computer 50 executes processing when the personal authentication is successful, such as unlocking the door.
  • the computer 50 executes a process when the personal authentication fails, for example, displaying a message indicating that the personal authentication failed on a display (not shown).
  • both processes may always be executed regardless of each collation result.
  • the other collation process in this case, vein collation process
  • the theoretical values obtained by the respective collation methods are weighted, and based on the values obtained by integrating the weighted theoretical values. It may be determined whether or not the verification is established.
  • theoretical values T1 and T2 representing the probability that the physical feature of the user who is the person to be authenticated is the physical feature of the user at the time of matching in each matching method are as follows. Ask for each. Then, the obtained theoretical values T1 and T2 are weighted, and when the value obtained by integrating the weighted theoretical values ⁇ T1 and (1- ⁇ ) T2 is larger than the threshold value S, it is determined that the collation is established.
  • the weight and threshold value can be set arbitrarily.
  • the pattern matching method is used as the first fingerprint matching method
  • the minutia method is used as the second fingerprint matching method
  • the direct comparison method is used as the first finger vein matching method
  • the second finger vein is used.
  • the feature amount method is exemplified as the matching method, it is needless to say that other matching methods (for example, a frequency analysis method in the case of the fingerprint matching method) may be adopted.
  • the first fingerprint verification method (or the first finger vein verification method) and the second fingerprint verification method (or the second finger vein verification method) are executed in this order. It is possible to arbitrarily set whether or not to execute. For example, a collation method with a high collation speed may be executed first, or a collation method with high collation accuracy may be executed first.
  • two types of collation methods are prepared for each of the fingerprint and the finger vein, but three or more types may be used.
  • any one of physical features for example, fingerprints
  • the verification method may be adopted.
  • the physical features used for collation are not limited to two types, and may be three or more types.
  • reflected light sensing is used for fingerprint matching and transmitted light sensing is used for finger vein matching.
  • transmitted light sensing is used for fingerprint matching and finger vein matching is performed. Reflected light sensing may be used, and how it is combined can be arbitrarily set.
  • the steps of each process shown in the present embodiment can be executed in any order or in parallel within a range where no contradiction occurs in the processing contents.
  • the term “means” does not simply mean a physical means, but includes a case where the functions of the means are realized by software.
  • the function of one means may be realized by two or more physical means, or the functions of two or more means may be realized by one physical means.
  • the software according to the present invention can be installed in a computer by downloading it through various recording media such as an optical disk such as a CD-ROM and a DVD-ROM, a magnetic disk, and a semiconductor memory, or via a communication network. Can be loaded.
  • the multimodal authentication device according to the present invention is suitable for improving both safety and convenience in personal authentication using two or more types of physical features.
  • DESCRIPTION OF SYMBOLS 100 Multimodal authentication apparatus, 40 ... Imaging device, 50 ... Computer, 510a ... Fingerprint collation means, 520a ... Fingerprint collation database, 510b ... Finger vein collation means, 520b ... Finger vein collation database, 530 ... Personal authentication means, MF1 ... First fingerprint verification module, MF2 ... second fingerprint verification module, TF1 ... first fingerprint verification template, TF2 ... second fingerprint verification template, MV1 ... first finger vein verification module, MV2 ... second finger Vein verification module, TV1... First finger vein verification template, TV2.

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Abstract

Disclosed is a multimodal authentication device wherein both safety and convenience are improved in personal authentication in which at least two types of physical features are used. The multimodal authentication device is provided with: a first matching means which applies a plurality of types of matching algorithms to determine whether or not a first physical feature of an authentication subject that is input is that of an authorized user; a second matching means which applies at least one type of matching algorithm to determine whether or not a second physical feature of the authentication subject that is input is that of an authorized user; and an authentication means which determines whether the authentication subject is an authorized user if a match is established in the first and second matching means. The first matching means determines that the first physical feature of the user that is input is that of an authorized user when a match is established in matching in which at least any one of the matching algorithms from among the plurality of types of matching algorithms is applied.

Description

マルチモーダル認証装置Multimodal authentication device
　本発明は、複数の身体的特徴を利用したマルチモーダル認証技術に関する。 The present invention relates to a multimodal authentication technique using a plurality of physical features.
　近年、指紋や指の静脈パターンなど、様々な身体的特徴を利用した認証技術が注目されている。このような認証技術においては、認証精度の向上が研究課題となっている。 In recent years, authentication technology using various physical features such as fingerprints and finger vein patterns has attracted attention. In such authentication technology, improvement of authentication accuracy is a research subject.
　かかる認証精度を向上する方法の一つとして、複数の身体的特徴を組み合わせて行うマルチモーダル生体認証システムが提案されている(例えば、特許文献１参照)。 As one method for improving the authentication accuracy, a multimodal biometric authentication system that combines a plurality of physical features has been proposed (see, for example, Patent Document 1).
　特許文献１によって提案された認証システムでは、２種類以上の認証方式（例えば、指紋認証方式や顔面認証方式等）を組み合わせ、登録者本人であるかどうかの確率をあらわす理論値を各認証方式により求め、論理演算の結果に基づき登録者本人であるか否かを判断する。 In the authentication system proposed by Patent Document 1, two or more types of authentication methods (for example, fingerprint authentication method, face authentication method, etc.) are combined, and a theoretical value representing the probability of whether or not the user is a registrant is used for each authentication method. It is determined whether or not the user is the registrant based on the result of the logical operation.
特開２０００－２４２７８６号公報JP 2000-242786 A
　しかしながら、いずれかの認証方式で認証が成功した場合に登録者本人と判断する場合には、攻撃者はいずれか１種類の認証方式に対応した身体的特徴(例えば指紋)を偽造すればよく、採用したすべての認証方式で認証が成功した場合にのみ登録者本人であると判断する場合と比較して安全性が低下するという問題がある。 However, when it is determined that the user is a registered person when the authentication is successful with any of the authentication methods, the attacker only has to forge a physical feature (for example, fingerprint) corresponding to any one of the authentication methods, There is a problem that safety is lowered compared to the case where it is determined that the user is the registrant only when the authentication is successful in all the adopted authentication methods.
　一方、すべての認証方式で認証が成功した場合にのみ登録者本人と判断する場合には、いずれかの認証方式で認証が失敗した場合に本人拒否と判断されるため、利便性が低下するという問題がある。 On the other hand, if it is determined that the registrant is the only person when authentication is successful in all authentication methods, the user is rejected if authentication fails in any of the authentication methods, which reduces convenience. There's a problem.
　本発明は、上述した事情を鑑みてなされたものであり、２種類以上の身体的特徴を利用した本人認証において、安全性と利便性との両方を向上させることが可能なマルチモーダル認証装置を提供することを目的とする。 The present invention has been made in view of the above-described circumstances, and provides a multimodal authentication apparatus capable of improving both safety and convenience in personal authentication using two or more types of physical features. The purpose is to provide.
　本発明に係るマルチモーダル認証装置は、入力される認証対象者の第１の身体的特徴について、複数種類の照合アルゴリズムを適用して正規ユーザのものであるか否かの判断を行う第１の照合手段と、入力される前記認証対象者の第２の身体的特徴について、１種類以上の照合アルゴリズムを適用して正規ユーザのものであるか否かの判断を行う第２の照合手段と、前記第１および第２の照合手段において照合が成立した場合に、前記認証対象者が正規ユーザであると判断する認証手段とを備え、前記第１の照合手段は、前記複数種類の照合アルゴリズムのうち、少なくともいずれか１つの照合アルゴリズムを適用した照合において照合が成立した場合に、入力される前記ユーザの第１の身体的特徴が正規ユーザのものであると判断することを特徴とする。 The multimodal authentication apparatus according to the present invention applies a plurality of types of matching algorithms to the first physical characteristics of the input authentication target person to determine whether or not the authentication target person belongs to a legitimate user. A second verification unit that applies one or more verification algorithms to determine whether or not the second physical feature of the input person to be authenticated is a regular user; Authentication means for determining that the person to be authenticated is a regular user when the first and second matching means are matched, and the first matching means includes the plurality of types of matching algorithms. Of these, when collation is established in the collation using at least one of the collation algorithms, it is determined that the first physical feature of the input user is that of the regular user. The features.
　また、本発明に係るマルチモーダル認証装置は、入力される認証対象者の第１の身体的特徴について、複数種類の照合アルゴリズムを適用して正規ユーザのものであるか否かの判断を行う第１の照合手段と、入力される前記認証対象者の第２の身体的特徴について、１種類以上の照合アルゴリズムを適用して正規ユーザのものであるか否かの判断を行う第２の照合手段と、前記第１および第２の照合手段において照合が成立した場合に、前記認証対象者が正規ユーザであると判断する認証手段とを備え、前記第１の照合手段は、前記複数種類の照合アルゴリズムを組み合わせ、各照合アルゴリズムを適用した場合に得られる、正規ユーザのものであるか否かを表す各理論値に重み付けを行い、重み付けした各理論値を統合した結果に基づいて照合が成立すると判断した場合に、入力される前記認証対象者の第１の身体的特徴が正規ユーザのものであると判断することを特徴とする。 In addition, the multimodal authentication apparatus according to the present invention applies a plurality of types of verification algorithms to determine whether or not the first physical feature of the input authentication target person belongs to the authorized user. And a second verification unit that determines whether or not the input second physical feature of the person to be authenticated is an authorized user by applying one or more verification algorithms. And an authentication means for determining that the person to be authenticated is a regular user when the first and second matching means are matched, wherein the first matching means includes the plurality of types of matching. Based on the result of combining each of the weighted theoretical values by weighting each theoretical value that represents whether or not the user is a regular user, obtained by combining algorithms and applying each matching algorithm If the verification is determined to be established, the first physical characteristic of the object's input to and determines that is legitimate user.
　さらに、本発明に係るマルチモーダル認証方法は、入力される認証対象者の第１の身体的特徴について、複数種類の照合アルゴリズムを適用して正規ユーザのものであるか否かの判断を行う照合ステップであって、前記複数種類の照合アルゴリズムのうち、少なくともいずれか１つの照合アルゴリズムを適用した照合において照合が成立した場合に、入力される前記ユーザの第１の身体的特徴が正規ユーザのものであると判断する第１の照合ステップと、入力される前記認証対象者の第２の身体的特徴について、１種類以上の照合アルゴリズムを適用して正規ユーザのものであるか否かの判断を行う第２の照合ステップと、前記第１および第２の照合ステップにおいて照合が成立した場合に、前記認証対象者が正規ユーザであると判断する認証ステップと、を含むことを特徴とする。 Further, the multimodal authentication method according to the present invention is a collation for determining whether or not the first physical feature of the input authentication target person belongs to a regular user by applying a plurality of types of collation algorithms. A first physical feature of the user that is input when the collation is established in the collation using at least one of the plural collation algorithms among the plurality of collation algorithms A first collation step for judging that the second physical feature of the person to be authenticated is applied and one or more collation algorithms are applied to determine whether or not the legitimate user belongs. When verification is established in the second verification step to be performed and the first and second verification steps, it is determined that the person to be authenticated is a regular user. Characterized in that it comprises a testimony step.
　本発明によれば、２種類以上の身体的特徴を利用した本人認証において、安全性と利便性との両方を向上させることが可能となる。 According to the present invention, it is possible to improve both safety and convenience in identity authentication using two or more types of physical features.
本実施形態に係るマルチモーダル認証装置の構成を示す図である。It is a figure which shows the structure of the multimodal authentication apparatus which concerns on this embodiment. 同実施形態に係るコンピュータの機能ブロックを示す図である。It is a figure which shows the functional block of the computer which concerns on the same embodiment. 同実施形態に係る反射光センシングの原理を示す図である。It is a figure which shows the principle of the reflected light sensing which concerns on the same embodiment. 同実施形態に係る透過光センシングの原理を示す図である。It is a figure which shows the principle of the transmitted light sensing which concerns on the same embodiment. 同実施形態に係る指紋画像を示す図である。It is a figure which shows the fingerprint image which concerns on the same embodiment. 同実施形態に係る指静脈画像を示す図である。It is a figure which shows the finger vein image which concerns on the same embodiment. 同実施形態に係る本人認証動作の概略を示す図である。It is a figure which shows the outline of the personal authentication operation | movement which concerns on the same embodiment. 同実施形態に係る指紋照合処理を示すフローチャートである。It is a flowchart which shows the fingerprint collation process which concerns on the embodiment. 同実施形態に係る指静脈照合処理を示すフローチャートである。It is a flowchart which shows the finger vein collation process which concerns on the same embodiment.
　以下、添付図面を参照して、本発明に係るマルチモーダル認証装置の好適な実施形態について説明する。 Hereinafter, preferred embodiments of a multimodal authentication device according to the present invention will be described with reference to the accompanying drawings.
Ａ．本実施形態
（１）実施形態の構成
　図１は、本実施形態に係るマルチモーダル認証装置１００の構成を示す図である。 A. Embodiment (1) Configuration of Embodiment FIG. 1 is a diagram illustrating a configuration of a multimodal authentication device 100 according to the present embodiment.
　マルチモーダル認証装置１００は、複数の身体的特徴（モダリティ）を組み合わせて認証を行う装置である。本実施形態では、複数のモダリティとして指紋と指静脈を利用する場合を想定するが、例えば指紋、顔画像、虹彩などの人物の身体形状をあらわす特徴（形状的特徴）を利用してもよく、また音声、手書きサイン、キータッチなどの人物の行動に基づく特徴（行動的特徴）を利用してもよい。なお、指紋と指静脈という身体的特徴の組み合わせや、顔と虹彩という身体的特徴の組み合わせは、それぞれ同一の身体的部位（指や顔）から得られるため、光学的センシングを行う場合にはこれらの情報を取得するセンサとして多くの部品を共通化でき、装置そのものを小型化できる等のメリットがある。さらに、認証対象者であるユーザは、認証のための入力動作が１回でよいため、簡単かつスピーディーに認証が行える等のメリットもある。 The multimodal authentication device 100 is a device that performs authentication by combining a plurality of physical features (modalities). In the present embodiment, it is assumed that fingerprints and finger veins are used as a plurality of modalities. For example, a feature (shape feature) representing a human body shape such as a fingerprint, a face image, and an iris may be used. Moreover, you may utilize the characteristic (behavioral characteristic) based on a person's action, such as a voice, a handwritten signature, and a key touch. Note that the combination of physical features of fingerprints and finger veins and the combination of physical features of faces and iris are obtained from the same physical part (finger or face). There are merits such that many parts can be used in common as a sensor for acquiring the information, and the apparatus itself can be miniaturized. Furthermore, since the user who is the subject of authentication needs only one input operation for authentication, there is an advantage that the authentication can be performed easily and speedily.
　図１に示すように、マルチモーダル認証装置１００は、上部筐体１０ａと、下部筐体１０ｂと、上部筐体１０ａに設けられた第１の光源３０ａと、下部筐体１０ｂに設けられた第２の光源３０ｂと、撮像装置（入力手段）４０と、コンピュータ５０を備えて構成される。マルチモーダル認証装置１００には、指と指静脈の各身体的特徴について、それぞれ２種類の照合方式が用意されている。いずれか一種類の照合方式で照合が成立した場合には、この身体的特徴については本人の身体的特徴であると判断する（詳細は後述）。以下、マルチモーダル認証装置１００の中枢を担うコンピュータ５０の機能について説明する。 As shown in FIG. 1, the multimodal authentication device 100 includes an upper housing 10a, a lower housing 10b, a first light source 30a provided in the upper housing 10a, and a first light source 30a provided in the lower housing 10b. 2 light sources 30 b, an imaging device (input means) 40, and a computer 50. In the multimodal authentication apparatus 100, two types of collation methods are prepared for each physical feature of the finger and the finger vein. When the collation is established by any one of the collation methods, it is determined that this physical feature is the physical feature of the person (details will be described later). Hereinafter, functions of the computer 50 serving as the center of the multimodal authentication device 100 will be described.
　図２は、コンピュータ５０の機能ブロック図である。 FIG. 2 is a functional block diagram of the computer 50.
　コンピュータ５０は、指紋照合手段５１０ａ、指紋照合データベース５２０ａ、指静脈照合手段５１０ｂ、指静脈照合データベース５２０ｂ、および本人認証手段５３０を備えて構成される。 The computer 50 includes a fingerprint collation unit 510a, a fingerprint collation database 520a, a finger vein collation unit 510b, a finger vein collation database 520b, and a personal authentication unit 530.
　指紋照合手段５１０ａは、撮像装置４０から出力される指紋画像に対応するユーザの指紋が、本人のものであるか否かを判断する。指紋照合手段５１０ａは、複数種類の指紋照合アルゴリズムを備えている。本実施形態では、指紋照合手段５１０ａは、画像パターンマッチング法によってユーザの指紋を照合するための第１の指紋照合モジュールＭＦ１と、マニューシャ法によってユーザの指紋を照合するための第２の指紋照合モジュールＭＦ２と、を備えている。 The fingerprint collation unit 510a determines whether or not the user's fingerprint corresponding to the fingerprint image output from the imaging device 40 is that of the user. The fingerprint collation unit 510a includes a plurality of types of fingerprint collation algorithms. In the present embodiment, the fingerprint verification unit 510a includes a first fingerprint verification module MF1 for verifying a user's fingerprint by an image pattern matching method and a second fingerprint verification module for verifying a user's fingerprint by a minutia method. MF2.
　指紋照合データベース５２０ａには、第１の指紋照合モジュール用の第１の指紋照合テンプレートＴＦ１と、第２の指紋照合モジュール用の第２の指紋照合テンプレートＴＦ２と、が登録されている。第１の指紋照合テンプレートＴＦ１と、第２の指紋照合テンプレートＴＦ２とには、それぞれ、正規ユーザ（ここでは本人）の指紋に対応する線画像と、本人の指紋のマニューシャ情報と、が登録されている。なお、本実施形態では正規ユーザが１人の場合を想定するが、正規ユーザは複数であってもよい。正規ユーザが複数いる場合には、正規ユーザごとに固有のユーザＩＤを割り当て、ユーザＩＤに対応付けて線画像を登録しておけばよい（この点は後述する他のテンプレートも同様である）。 In the fingerprint verification database 520a, a first fingerprint verification template TF1 for the first fingerprint verification module and a second fingerprint verification template TF2 for the second fingerprint verification module are registered. In the first fingerprint matching template TF1 and the second fingerprint matching template TF2, a line image corresponding to the fingerprint of the authorized user (here, the principal) and minutia information of the principal's fingerprint are registered. Yes. In the present embodiment, it is assumed that there is one authorized user, but there may be a plurality of authorized users. When there are a plurality of regular users, a unique user ID may be assigned to each regular user, and a line image may be registered in association with the user ID (this is the same for other templates described later).
　指静脈照合手段５１０ｂは、撮像装置４０から出力される指静脈画像に対応するユーザの血管パターン（静脈パターン）が、本人のものであるか否かを判断する。指静脈照合手段５１０ｂは、複数種類の指静脈照合アルゴリズムを備えている。本実施形態では、指静脈照合手段５１０ｂは、パターンマッチング方式によってユーザの指静脈を照合するための第１の指静脈照合モジュールと、特徴量方式によってユーザの指静脈を照合するための第２の指静脈照合モジュールと、を備えている。 The finger vein collating means 510b determines whether or not the user's blood vessel pattern (vein pattern) corresponding to the finger vein image output from the imaging device 40 is that of the user. The finger vein matching unit 510b includes a plurality of types of finger vein matching algorithms. In the present embodiment, the finger vein matching unit 510b includes a first finger vein matching module for matching the user's finger vein by the pattern matching method and a second finger vein for matching the user's finger vein by the feature amount method. A finger vein verification module.
　指静脈照合データベース５２０ｂには、第１の指静脈照合モジュール用の第１の指静脈照合テンプレートＴＶ１と、第２の指静脈照合モジュール用の第２の指静脈照合テンプレートＴＶ２と、が登録されている。第１の指静脈照合テンプレートＴＶ１と、第２の指静脈照合テンプレートＴＶ２とには、それぞれ、本人の血管パターンをあらわす画像と、本人の血管パターンの特徴量と、が登録されている。 In the finger vein matching database 520b, a first finger vein matching template TV1 for the first finger vein matching module and a second finger vein matching template TV2 for the second finger vein matching module are registered. Yes. In the first finger vein matching template TV1 and the second finger vein matching template TV2, an image representing the blood vessel pattern of the person and the feature amount of the blood vessel pattern of the person are registered.
　本人認証手段５３０は、指紋照合手段５１０ａの照合結果と指静脈照合手段５１０ｂの照合結果とを受け取り、本人認証を行う。具体的には、本人認証手段５３０は、指紋の照合結果と血管パターンの照合結果とを、ＡＮＤ型統合することで（図５のγ参照）、指紋照合および静脈照合の両照合が成立した場合にのみ、被認証者が本人であると判断する。以下、本実施形態に係る指紋照合および指静脈照合の特徴について説明する。 The personal authentication unit 530 receives the verification result of the fingerprint verification unit 510a and the verification result of the finger vein verification unit 510b, and performs personal authentication. Specifically, the personal authentication unit 530 performs AND type integration of the fingerprint matching result and the blood vessel pattern matching result (see γ in FIG. 5), and when both fingerprint matching and vein matching are established. Only when the person to be authenticated is determined to be the person. Hereinafter, features of fingerprint matching and finger vein matching according to the present embodiment will be described.
＜指紋照合＞
　図３Ａは、マルチモーダル認証装置１００によって実現される反射光センシングの原理を示す図である。 <Fingerprint verification>
FIG. 3A is a diagram illustrating the principle of reflected light sensing realized by the multimodal authentication device 100.
　マルチモーダル認証装置１００は、下部筐体１０ｂに設けられた第２の光源３０ｂと撮像装置４０によって反射光センシングを行い、図４Ａに示すような指紋画像を得る。具体的には、皮膚が盛り上がった隆線ＲＬが明るく、その間の谷線ＶＬが暗い指紋画像が得られる（図４Ａ参照）。 The multimodal authentication device 100 performs reflected light sensing with the second light source 30b and the imaging device 40 provided in the lower housing 10b, and obtains a fingerprint image as shown in FIG. 4A. Specifically, a fingerprint image in which the ridge RL where the skin is raised is bright and the valley line VL in between is dark (see FIG. 4A).
　画像パターンマッチング法の照合アルゴリズムは、撮像装置４０によって得られた指紋画像に対して２値化等の画像処理を施すことにより隆線パターンを線画像として抽出し、抽出した線画像を用いて照合するアルゴリズムである。 The matching algorithm of the image pattern matching method extracts a ridge pattern as a line image by performing image processing such as binarization on the fingerprint image obtained by the imaging device 40, and performs matching using the extracted line image. It is an algorithm to do.
　画像パターンマッチング法は、従来から良く知られているように、第１の指紋照合テンプレートＴＦ１に登録されている本人の指紋に対応する画像と、照合時に第１の指紋照合モジュールＭＦ１によって得られる線画像と、を直接比較し、その類似度を算出することにより、本人の指紋であるか否かを判断する。 As is well known in the art, the image pattern matching method uses an image corresponding to the fingerprint of the person registered in the first fingerprint matching template TF1 and a line obtained by the first fingerprint matching module MF1 at the time of matching. By directly comparing the image and calculating the similarity, it is determined whether or not it is the fingerprint of the user.
　一方、マニューシャ法の照合アルゴリズムは、撮像装置４０によって得られた指紋画像からマニューシャ（特徴点）を抽出し、例えばマニューシャの位置や種類、方向などのマニューシャ情報を用いて照合するアルゴリズムである。 On the other hand, the matching algorithm of the minutia method is an algorithm that extracts minutiae (feature points) from the fingerprint image obtained by the imaging device 40 and collates using minutiae information such as the position, type, and direction of the minutiae.
　マニューシャ法もまた、従来から良く知られているように、第２の指紋照合テンプレートＴＦ２に登録されている本人の指紋に対応するマニューシャ情報と、照合時に第２の指紋照合モジュールＭＦ２によって得られるマニューシャ情報と、を比較することにより、本人の指紋であるか否かを判断する。 As well known in the art, the minutia method is also well known in the art, the minutia information corresponding to the fingerprint of the person registered in the second fingerprint collation template TF2, and the minutiae obtained by the second fingerprint collation module MF2 at the time of collation. By comparing the information, it is determined whether or not it is the fingerprint of the person.
　本実施形態では、２種類の指紋照合方式（具体的には画像パターンマッチング法およびマニューシャ法）をＯＲ型統合することで（図５のα参照）、いずれか１つの指紋照合方式で照合が成立すれば本人の指紋（第１の身体的特徴）であると判断する。 In this embodiment, two types of fingerprint matching methods (specifically, the image pattern matching method and the minutiae method) are OR-integrated (see α in FIG. 5), and matching is established by any one of the fingerprint matching methods. Then, it is determined that the fingerprint is the person's fingerprint (first physical characteristic).
＜静脈照合＞
　図３Ｂは、マルチモーダル認証装置１００によって実現される透過光センシングの原理を示す図である。 <Venous verification>
FIG. 3B is a diagram illustrating the principle of transmitted light sensing realized by the multimodal authentication device 100.
　マルチモーダル認証装置１００は、上部筐体１０ａに設けられた第１の光源３０ａと撮像装置４０によって透過光センシングを行い、図４Ｂに示すような指静脈画像を得る。具体的には、近赤外光が血液中のヘモグロビンにより吸収されることで血管部分ＢＡが暗く、その他の部分が明るい指静脈画像が得られる（図４Ｂ参照）。 The multimodal authentication device 100 performs transmitted light sensing using the first light source 30a and the imaging device 40 provided in the upper housing 10a, and obtains a finger vein image as shown in FIG. 4B. Specifically, a finger vein image in which the blood vessel portion BA is dark and the other portions are bright is obtained by absorbing near-infrared light by hemoglobin in the blood (see FIG. 4B).
　画像パターンマッチング方式の認証アルゴリズムは、撮像装置４０によって得られる指静脈画像に対して画像処理を施すことにより、血管パターンを抽出し、抽出した血管パターンをあらわす画像を照合するアルゴリズムである。 The authentication algorithm of the image pattern matching method is an algorithm for extracting a blood vessel pattern by performing image processing on the finger vein image obtained by the imaging device 40 and collating an image representing the extracted blood vessel pattern.
　画像パターンマッチング方式は、従来から良く知られているように、第１の指静脈照合テンプレートＴＶ１に登録されている本人（ユーザ）の血管パターンをあらわす画像と、照合時に第１の指静脈照合モジュールＭＶ１によって得られる線画像と、を直接比較することで、本人の血管パターン（静脈パターン）であるか否かを判断する。 As is well known in the art, the image pattern matching method includes an image representing the blood vessel pattern of the person (user) registered in the first finger vein matching template TV1 and the first finger vein matching module at the time of matching. By directly comparing the line image obtained by the MV1, it is determined whether or not the blood vessel pattern (vein pattern) of the user.
　一方、特徴量方式の照合アルゴリズムは、撮像装置４０によって得られる指静脈画像に対して画像処理を施すことにより、血管部分を細線化したのち、分岐点から分岐点へと順次分岐点間の線をたどり、分岐点の座標、長さ、分岐点における分岐角度などの特徴量を抽出し、抽出した特徴量を照合するアルゴリズムである。 On the other hand, the collation algorithm of the feature amount method performs image processing on the finger vein image obtained by the imaging device 40, thereby thinning the blood vessel portion and then sequentially connecting the lines between the branch points from the branch points to the branch points. Are extracted, feature quantities such as branch point coordinates, length, branch angle at the branch point, etc. are extracted, and the extracted feature quantities are collated.
　特徴量方式もまた、従来から良く知られているように、第２の指静脈照合テンプレートＴＶ２に登録されている本人の血管パターンの特徴量と、照合時に第２の指静脈照合モジュールＭＶ２によって得られる血管パターンの特徴量と、を比較することにより、本人の血管パターン（静脈パターン）であるか否かを判断する。 As is well known in the art, the feature amount method is also obtained by the second finger vein matching module MV2 at the time of matching with the feature amount of the person's blood vessel pattern registered in the second finger vein matching template TV2. It is determined whether or not the blood vessel pattern (vein pattern) of the person is by comparing the characteristic amount of the blood vessel pattern to be obtained.
　以上説明した２種類の指静脈照合方式（具体的には、画像パターンマッチング方式および特徴量方式）についても、上述した２種類の指紋照合方式と同様、ＯＲ型統合することで（図５のβ参照）、いずれか１つの指静脈照合方式で照合が成立すれば本人の血管パターン（静脈パターン；第２の身体的特徴）であると判断する。 The two types of finger vein matching methods described above (specifically, the image pattern matching method and the feature amount method) are also integrated by OR type integration (β in FIG. If the collation is established by any one of the finger vein collation methods, it is determined that the blood vessel pattern (vein pattern; second physical feature) of the person.
　そして、最後に、指紋の照合結果と血管パターンの照合結果とをＡＮＤ型統合することで（図５のγ参照）、指紋照合および静脈照合の両方において本人であると判断した場合にのみ、指紋画像および指静脈画像を取得したユーザ（被認証者）が本人であると判断する。 Finally, the fingerprint matching result and the blood vessel pattern matching result are AND-type integrated (see γ in FIG. 5), and only when it is determined that the person is the person in both fingerprint matching and vein matching. It is determined that the user (authenticated person) who acquired the image and the finger vein image is the person himself / herself.
　このように、身体的特徴（モダリティ）ごとに複数の照合方式を用意し、いずれかの方式で照合が成立した場合、この身体的特徴（例えば指紋）については本人のものであると判断する（図５のα、βに示すＯＲ型統合参照）。これにより、１つの照合方式を利用して身体的特徴を照合していた従来例と比較して、本人拒否の確率を低減することが可能となる。 As described above, when a plurality of collation methods are prepared for each physical feature (modality) and collation is established by any of the methods, it is determined that the physical feature (for example, fingerprint) belongs to the person ( (Refer to OR type integration indicated by α and β in FIG. 5). This makes it possible to reduce the probability of rejecting the person as compared with the conventional example in which the physical features are collated using one collation method.
　また、全ての身体的特徴（例えば指紋と指静脈）について本人のものであると判断した場合にのみ、被認証者が本人であると判断するため、攻撃者は本人の身体的特徴を全て偽造しなければならず、なりすましが困難となり、安全性を向上させることが可能となる。 In addition, only when it is determined that all physical characteristics (for example, fingerprints and finger veins) belong to the person in question, the attacker determines that the person to be authenticated is the person himself. Therefore, impersonation becomes difficult, and safety can be improved.
　（２）実施形態の動作
　被認証者であるユーザは、マルチモーダル認証装置１００の上部筐体１０ａと下部筐体１０ｂとの間に指を入れ、指の腹を下部筐体１０ｂのテンプレートＴＥに載置する（図１参照）。マルチモーダル認証装置１００は、テンプレートＴＥにユーザの指の腹が載置されたことを検知すると、下部筐体１０ｂに設けられた第２の光源３０ｂおよび撮像装置４０によって反射光センシングを行い、図３Ａに示すような指紋画像を取得する。一方、上部筐体１０ａに設けられた第１の光源３０ａと撮像装置４０とによって透過光センシングを行い、図３Ｂに示すような指静脈画像を取得する。撮像装置４０は、取得した指紋画像と指静脈画像とをコンピュータ５０に送信する。なお、本実施形態では、センサ面（テンプレートＴＥ）に指を接触させて画像を取得する場合（接触式センサを利用する場合）を想定するが、センサとして非接触のもの（すなわち非接触式センサ）を対象としても良い。非接触式センサを利用する場合にはテンプレートＴＥは不要である。テンプレートＴＥがない場合に、指が所定の位置に存在するか否かを判定する方法としては、例えば連続して取得される画像を時系列に並べて比較する方法を採用することができる。 (2) Operation of Embodiment A user who is an authentication target puts a finger between the upper housing 10a and the lower housing 10b of the multimodal authentication device 100, and the belly of the finger is placed on the template TE of the lower housing 10b. Place (see FIG. 1). When the multimodal authentication device 100 detects that the user's finger belly is placed on the template TE, the multimodal authentication device 100 performs reflected light sensing using the second light source 30b and the imaging device 40 provided in the lower housing 10b. A fingerprint image as shown in 3A is acquired. On the other hand, transmitted light sensing is performed by the first light source 30a and the imaging device 40 provided in the upper housing 10a, and a finger vein image as shown in FIG. 3B is acquired. The imaging device 40 transmits the acquired fingerprint image and finger vein image to the computer 50. In this embodiment, it is assumed that an image is acquired by bringing a finger into contact with the sensor surface (template TE) (when a contact sensor is used), but the sensor is a non-contact sensor (that is, a non-contact sensor). ). When using a non-contact sensor, the template TE is not necessary. As a method for determining whether or not the finger is present at a predetermined position when there is no template TE, for example, a method in which images obtained successively are arranged in time series and compared can be employed.
＜指紋照合処理＞
　図６は、マルチモーダル認証装置１００を用いた指紋照合処理を示すフローチャートである。 <Fingerprint verification process>
FIG. 6 is a flowchart showing fingerprint collation processing using the multimodal authentication device 100.
　コンピュータ５０の指紋照合手段５１０ａは、撮像装置４０からユーザの指紋画像を受け取ると（ステップＳ１ａ）、第１の指紋照合モジュール（画像パターンマッチング法）ＭＦ１を利用し、撮像装置４０から出力される指紋画像に対応するユーザの指紋が、本人のものであるか否かを判断（照合）する（ステップＳ２ａ）。指紋照合手段５１０ａは、第１の指紋照合モジュールＭＦ１を利用した指紋照合により、被認証者であるユーザの指紋が本人の指紋であると判断（すなわち、照合が成立）すると（ステップＳ３ａ；ＹＥＳ）、第２の指紋照合モジュール（マニューシャ法）ＭＦ２を利用した照合を行うことなく、ステップＳ６ａに進む。 When the fingerprint verification unit 510a of the computer 50 receives the fingerprint image of the user from the imaging device 40 (step S1a), the fingerprint output from the imaging device 40 using the first fingerprint verification module (image pattern matching method) MF1. It is determined (collated) whether or not the user's fingerprint corresponding to the image is that of the user (step S2a). When the fingerprint collation unit 510a determines that the fingerprint of the user who is the person to be authenticated is the fingerprint of the user (ie, collation is established) by fingerprint collation using the first fingerprint collation module MF1 (step S3a; YES) The process proceeds to step S6a without performing collation using the second fingerprint collation module (maneuver method) MF2.
　このように、第１の指紋照合モジュールＭＦ１を利用した照合が成立すると、第２の指紋照合モジュールＭＦ２を利用した照合を行わない理由は次のとおりである。本実施形態では、いずれか一方の指紋照合方式で照合が成立した場合に、ユーザの指紋が本人のものであると判断するため（図５α参照）、第１の指紋照合モジュールＭＦ１を利用した照合が成立すれば、これ以上、照合を行う必要がないからである。かかる構成を採用することで、照合速度を向上させることができるとともに、処理の簡素化を図ることができる。 As described above, when collation using the first fingerprint collation module MF1 is established, the collation using the second fingerprint collation module MF2 is not performed as follows. In the present embodiment, when the collation is established by any one of the fingerprint collation methods, the collation using the first fingerprint collation module MF1 is performed in order to determine that the user's fingerprint is the original person (see FIG. 5α). This is because there is no need for further verification if the above holds. By adopting such a configuration, the verification speed can be improved and the processing can be simplified.
　一方、第１の指紋照合モジュールＭＦ１を利用した照合が成立しない場合には（ステップＳ３ａ；ＮＯ）、第２の指紋照合モジュール（マニューシャ法）ＭＦ２を利用し、撮像装置４０から出力される指紋画像に対応するユーザの指紋が、本人のものであるか否かを判断（照合）する（ステップＳ４ａ）。指紋照合手段５１０ａは、第２の指紋照合モジュールＭＦ２を利用した指紋照合により、被認証者であるユーザの指紋が本人の指紋であると判断（すなわち、照合が成立）すると（ステップＳ５ａ；ＹＥＳ）、本人認証手段５３０に照合が成立した旨を通知し（ステップＳ６ａ）、処理を終了する。一方、指紋照合手段５１０ａは、第２の指紋照合モジュールを利用した照合が成立しない場合には（ステップＳ５ａ；ＮＯ）、本人認証手段５３０に照合が成立しなかった旨を通知し（ステップＳ７ａ）、処理を終了する。 On the other hand, when collation using the first fingerprint collation module MF1 is not established (step S3a; NO), the fingerprint image output from the imaging device 40 using the second fingerprint collation module (maneuver method) MF2 is used. It is judged (verified) whether or not the user's fingerprint corresponding to is the person's own (step S4a). When the fingerprint collation unit 510a determines that the fingerprint of the user who is the person to be authenticated is the fingerprint of the user (that is, collation is established) by fingerprint collation using the second fingerprint collation module MF2 (step S5a; YES) Then, the personal authentication means 530 is notified that the verification has been established (step S6a), and the process is terminated. On the other hand, when the collation using the second fingerprint collation module is not established (step S5a; NO), the fingerprint collation means 510a notifies the personal authentication means 530 that the collation is not established (step S7a). The process is terminated.
＜指静脈照合処理＞
　図７は、マルチモーダル認証装置１００を用いた指静脈照合処理を示すフローチャートである。 <Finger vein verification process>
FIG. 7 is a flowchart showing finger vein collation processing using the multimodal authentication device 100.
　コンピュータ５０の指静脈照合手段５１０ｂは、撮像装置４０からユーザの指静脈画像を受け取ると（ステップＳ１ｂ）、第１の指静脈照合モジュール（画像パターンマッチング方式）ＭＶ１を利用し、撮像装置４０から出力される指静脈画像に対応するユーザの血管パターン（静脈パターン）が、本人のものであるか否かを判断（照合）する（ステップＳ２ｂ）。指静脈照合手段５１０ｂは、第１の指静脈照合モジュールＭＶ１を利用した静脈照合により、被認証者であるユーザの血管パターンが本人の血管パターンであると判断（すなわち、照合が成立）すると（ステップＳ３ｂ；ＹＥＳ）、第２の指静脈照合モジュール（特徴量方式）ＭＶ２を利用した照合を行うことなく、ステップＳ６ｂに進む。 When the finger vein collating unit 510b of the computer 50 receives the finger vein image of the user from the imaging device 40 (step S1b), the finger vein matching unit 510b outputs the image from the imaging device 40 using the first finger vein matching module (image pattern matching method) MV1. It is determined (collated) whether or not the user's blood vessel pattern (vein pattern) corresponding to the finger vein image to be processed is the user's own (step S2b). When the vein verification using the first finger vein verification module MV1 determines that the blood vessel pattern of the user who is the person to be authenticated is the blood vessel pattern of the user (that is, the verification is established) S3b; YES), the process proceeds to step S6b without performing collation using the second finger vein collation module (feature quantity method) MV2.
　このように、第１の指静脈照合モジュールＭＶ１を利用した照合が成立すると、第２の指静脈照合モジュールＭＶ２を利用した照合を行わない理由は、上述した指紋照合の場合と同様、いずれか一方の指静脈照合方式で照合が成立した場合には、ユーザの血管パターンが本人のものであると判断するため（図５β参照）、第１の指静脈照合モジュールＭＶ１を利用した照合が成立すれば、これ以上、照合を行う必要がないからである。 As described above, when collation using the first finger vein collation module MV1 is established, the reason why collation using the second finger vein collation module MV2 is not performed is the same as in the case of the fingerprint collation described above. When the collation is established by the finger vein collation method, the user's blood vessel pattern is determined to be the person's own (see FIG. 5β), so that the collation using the first finger vein collation module MV1 is established. This is because there is no need for further verification.
　一方、第１の指静脈照合モジュールＭＶ１を利用した照合が成立しない場合には（ステップＳ３ｂ；ＮＯ）、第２の指静脈照合モジュール（特徴量方式）ＭＶ２を利用し、撮像装置４０から出力される指静脈画像に対応するユーザの血管パターン（静脈パターン）が、本人のものであるか否かを判断（照合）する（ステップＳ４ｂ）。指静脈照合手段５１０ｂは、第２の指静脈照合モジュールＭＶ２を利用した静脈照合により、被認証者であるユーザの血管パターンが本人の血管パターンであると判断（すなわち、照合が成立）すると（ステップＳ５ｂ；ＹＥＳ）、本人認証手段５３０に照合が成立した旨を通知し（ステップＳ６ｂ）、処理を終了する。一方、指静脈照合手段５１０ｂは、第２の指静脈照合モジュールＭＶ２を利用した照合が成立しない場合には（ステップＳ５ｂ；ＮＯ）、本人認証手段５３０に照合が成立しなかった旨を通知し（ステップＳ７ｂ）、処理を終了する。 On the other hand, when collation using the first finger vein collation module MV1 is not established (step S3b; NO), the second finger vein collation module (feature amount method) MV2 is used and output from the imaging device 40. It is determined (collated) whether or not the user's blood vessel pattern (vein pattern) corresponding to the finger vein image is that of the user (step S4b). When the finger vein matching unit 510b determines that the blood vessel pattern of the user who is the person to be authenticated is the blood vessel pattern of the user by the vein matching using the second finger vein matching module MV2 (that is, the matching is established) (step S1). S5b; YES), the personal authentication means 530 is notified that the verification has been established (step S6b), and the process is terminated. On the other hand, when the verification using the second finger vein verification module MV2 is not established (step S5b; NO), the finger vein verification unit 510b notifies the personal authentication unit 530 that the verification has not been established ( Step S7b), the process is terminated.
　本人認証手段５３０は、指紋照合手段５１０ａから受け取った指紋の照合結果と、指静脈照合手段５１０ｂから受け取った指静脈の照合結果と、をＡＮＤ型統合することで（図５のγ参照）、指紋の照合および指静脈の照合の両照合が成立した場合にのみ、被認証者であるユーザが本人であると判断する。 The personal authentication unit 530 AND-integrates the fingerprint verification result received from the fingerprint verification unit 510a and the finger vein verification result received from the finger vein verification unit 510b (see [gamma] in FIG. 5). Only when both of the above verification and finger vein verification are established, the user who is the person to be authenticated is determined to be the person himself / herself.
　本人認証が成功した場合、コンピュータ５０は、例えばドアを解錠するなど、本人認証に成功した場合の処理を実行する。一方、本人認証が失敗した場合には、コンピュータ５０は、例えば本人認証に失敗した旨のメッセージをディスプレイ（図示略）に表示するなど、本人認証に失敗した場合の処理を実行する。 When the personal authentication is successful, the computer 50 executes processing when the personal authentication is successful, such as unlocking the door. On the other hand, when the personal authentication fails, the computer 50 executes a process when the personal authentication fails, for example, displaying a message indicating that the personal authentication failed on a display (not shown).
　なお、以上説明した指紋照合処理（図６参照）および静脈照合処理（図７参照）に関し、各照合結果にかかわらず常に両処理を実行してもよいが、いずれか一方の照合処理(例えば指紋照合処理)で照合が成立しない場合には、他方の照合処理（この場合は静脈照合処理）を省略することとしてもよい。 In addition, regarding the fingerprint collation process (see FIG. 6) and the vein collation process (see FIG. 7) described above, both processes may always be executed regardless of each collation result. When collation is not established in the collation process), the other collation process (in this case, vein collation process) may be omitted.
Ｂ．変形例
　（１）上述した本実施形態では、身体的特徴（モダリティ）ごとに２種類の照合方式を用意し、各身体的特徴についていずれか一方の照合方式で照合が成立（すなわち、被認証者であるユーザの身体的特徴が本人の身体的特徴であると判断）した場合には、他の照合方式での照合を省略しているが（図６、図７参照）、省略せずに各身体的特徴について２種類（全て）の照合方式を実行することとしてもよい。 B. Modifications (1) In the above-described embodiment, two types of collation methods are prepared for each physical feature (modality), and collation is established for each physical feature using one of the collation methods (that is, the person to be authenticated) (If it is determined that the physical characteristics of the user are the physical characteristics of the user), collation with other collation methods is omitted (see FIGS. 6 and 7). It is good also as performing two types (all) collation systems about a physical feature.
　ここで、全ての照合方式（ここでは２種類の照合方式を想定）を実行する場合に、各照合方式により求めた理論値に重み付けを行い、重み付けを行った各理論値を統合した値に基づいて照合が成立するか否かを判断してもよい。具体的には、下記式（Ａ）に示すように、各照合方式での照合時に、被認証者であるユーザの身体的特徴が本人の身体的特徴である確率をあらわす理論値Ｔ１、Ｔ２をそれぞれ求める。そして、求めた理論値Ｔ１、Ｔ２に重み付けを行い、重み付けを行った各理論値αＴ１、（１-α）Ｔ２を統合した値が閾値Ｓよりも大きい場合に照合成立と判断する。なお、重みや閾値については任意に設定可能である。 Here, when all the collation methods (here, two types of collation methods are assumed), the theoretical values obtained by the respective collation methods are weighted, and based on the values obtained by integrating the weighted theoretical values. It may be determined whether or not the verification is established. Specifically, as shown in the following formula (A), theoretical values T1 and T2 representing the probability that the physical feature of the user who is the person to be authenticated is the physical feature of the user at the time of matching in each matching method are as follows. Ask for each. Then, the obtained theoretical values T1 and T2 are weighted, and when the value obtained by integrating the weighted theoretical values αT1 and (1-α) T2 is larger than the threshold value S, it is determined that the collation is established. The weight and threshold value can be set arbitrarily.
　αＴ１＋（１－α）Ｔ２＞Ｓ　・・・（Ａ）
　Ｔ１、Ｔ２；理論値
　α；重み（０＜α＜１）
　Ｓ：閾値 αT1 + (1-α) T2> S (A)
T1, T2; theoretical value α; weight (0 <α <1)
S: threshold
　（２）また、本実施形態では、便宜上、第１の指紋照合方式としてパターンマッチング法、第２の指紋照合方式としてマニューシャ法、第１の指静脈照合方式として直接比較方式、第２の指静脈照合方式として特徴量方式を例示したが、他の照合方式（例えば指紋照合方式であれば周波数解析法など）を採用してもよいのはもちろんである。また、本実施形態では、第１の指紋照合方式（または第１の指静脈照合方式）、第２の指紋照合方式（または第２の指静脈照合方式）の順番で実行したが、いずれの順番で実行するのかは任意に設定可能である。例えば、照合速度の速い照合方式を先に実行してもよく、また照合精度の高い照合方式を先に実行してもよい。 (2) In this embodiment, for convenience, the pattern matching method is used as the first fingerprint matching method, the minutia method is used as the second fingerprint matching method, the direct comparison method is used as the first finger vein matching method, and the second finger vein is used. Although the feature amount method is exemplified as the matching method, it is needless to say that other matching methods (for example, a frequency analysis method in the case of the fingerprint matching method) may be adopted. In this embodiment, the first fingerprint verification method (or the first finger vein verification method) and the second fingerprint verification method (or the second finger vein verification method) are executed in this order. It is possible to arbitrarily set whether or not to execute. For example, a collation method with a high collation speed may be executed first, or a collation method with high collation accuracy may be executed first.
　（３）さらに、本実施形態では、指紋、指静脈のそれぞれについて、照合方式を２種類ずつ用意したが、３種類以上であってもよい。さらに、いずれか一つの身体的特徴（例えば指紋）について、複数種類（すなわち２種類以上）の照合方式を採用していれば良く、他の身体的特徴（例えば指静脈）についてはいずれか１種類の照合方式を採用してもよい。もちろん、照合に利用する身体的特徴は２種類に限定されず、３種類以上であってもよい。また、本実施形態では、指紋照合に反射光センシングを利用し、指静脈照合に透過光センシングを利用したが、これとは逆に、指紋照合に透過光センシングを利用し、指静脈照合については反射光センシングを利用してもよく、どのように組み合わせるかは任意に設定可能である。 (3) Furthermore, in this embodiment, two types of collation methods are prepared for each of the fingerprint and the finger vein, but three or more types may be used. Furthermore, any one of physical features (for example, fingerprints) may be adopted by using a plurality of types (ie, two or more types) of collation methods, and any other physical features (for example, finger veins) may be selected. The verification method may be adopted. Of course, the physical features used for collation are not limited to two types, and may be three or more types. In this embodiment, reflected light sensing is used for fingerprint matching and transmitted light sensing is used for finger vein matching. Conversely, transmitted light sensing is used for fingerprint matching and finger vein matching is performed. Reflected light sensing may be used, and how it is combined can be arbitrarily set.
　また、本実施形態において示した各処理のステップは処理内容に矛盾を生じない範囲で任意に順番を変更してまたは並列に実行することができる。さらに本明細書等において、手段とは、単に物理的手段を意味するものではなく、その手段が有する機能をソフトウェアによって実現する場合も含む。さらにまた、１つの手段が有する機能が２つ以上の物理的手段により実現されても、２つ以上の手段の機能が１つの物理的手段により実現されてもよい。また、本発明に係るソフトウェアは、ＣＤ－ＲＯＭやＤＶＤ－ＲＯＭ等の光学ディスク、磁気ディスク、半導体メモリなどの各種の記録媒体を通じて、または通信ネットワークなどを介してダウンロードすることにより、コンピュータにインストールまたはロードすることができる。 In addition, the steps of each process shown in the present embodiment can be executed in any order or in parallel within a range where no contradiction occurs in the processing contents. Furthermore, in this specification and the like, the term “means” does not simply mean a physical means, but includes a case where the functions of the means are realized by software. Furthermore, the function of one means may be realized by two or more physical means, or the functions of two or more means may be realized by one physical means. In addition, the software according to the present invention can be installed in a computer by downloading it through various recording media such as an optical disk such as a CD-ROM and a DVD-ROM, a magnetic disk, and a semiconductor memory, or via a communication network. Can be loaded.
　この出願は、２００９年１１月１７日に出願された日本出願特願２００９－２６２１６７を基礎とする優先権を主張し、その開示の全てをここに取り込む。 This application claims priority based on Japanese Patent Application No. 2009-262167 filed on November 17, 2009, the entire disclosure of which is incorporated herein.
　以上、実施形態を参照して本発明を説明したが、本発明は上記実施形態に限定されるものではない。本発明の構成や詳細には、本発明のスコープ内で当業者が理解し得る様々な変更をすることができる。 The present invention has been described above with reference to the embodiments, but the present invention is not limited to the above embodiments. Various changes that can be understood by those skilled in the art can be made to the configuration and details of the present invention within the scope of the present invention.
　本発明に係るマルチモーダル認証装置は、２種類以上の身体的特徴を利用した本人認証において、安全性と利便性との両方を向上させることに適している。 The multimodal authentication device according to the present invention is suitable for improving both safety and convenience in personal authentication using two or more types of physical features.
１００…マルチモーダル認証装置、４０…撮像装置、５０…コンピュータ、５１０ａ…指紋照合手段、５２０ａ…指紋照合データベース、５１０ｂ…指静脈照合手段、５２０ｂ…指静脈照合データベース、５３０…本人認証手段、ＭＦ１…第１の指紋照合モジュール、ＭＦ２…第２の指紋照合モジュール、ＴＦ１…第１の指紋照合テンプレート、ＴＦ２…第２の指紋照合テンプレート、ＭＶ１…第１の指静脈照合モジュール、ＭＶ２…第２の指静脈照合モジュール、ＴＶ１…第１の指静脈照合テンプレート、ＴＶ２…第２の指静脈照合テンプレート。 DESCRIPTION OF SYMBOLS 100 ... Multimodal authentication apparatus, 40 ... Imaging device, 50 ... Computer, 510a ... Fingerprint collation means, 520a ... Fingerprint collation database, 510b ... Finger vein collation means, 520b ... Finger vein collation database, 530 ... Personal authentication means, MF1 ... First fingerprint verification module, MF2 ... second fingerprint verification module, TF1 ... first fingerprint verification template, TF2 ... second fingerprint verification template, MV1 ... first finger vein verification module, MV2 ... second finger Vein verification module, TV1... First finger vein verification template, TV2.

Claims (7)

  1. 　入力される認証対象者の第１の身体的特徴について、複数種類の照合アルゴリズムを適用して正規ユーザのものであるか否かの判断を行う第１の照合手段と、
    　入力される前記認証対象者の第２の身体的特徴について、１種類以上の照合アルゴリズムを適用して正規ユーザのものであるか否かの判断を行う第２の照合手段と、
    　前記第１および第２の照合手段において照合が成立した場合に、前記認証対象者が正規ユーザであると判断する認証手段とを備え、
    　前記第１の照合手段は、前記複数種類の照合アルゴリズムのうち、少なくともいずれか１つの照合アルゴリズムを適用した照合において照合が成立した場合に、入力される前記ユーザの第１の身体的特徴が正規ユーザのものであると判断する、
    　マルチモーダル認証装置。     A first verification unit that determines whether or not the first physical feature of the input person to be authenticated belongs to an authorized user by applying a plurality of types of verification algorithms;
    A second verification unit that determines whether or not the second physical feature of the authentication target person is an authorized user by applying one or more verification algorithms;
    Authentication means for determining that the person to be authenticated is a regular user when the first and second matching means are matched;
    The first collating means is configured such that, when collation is established in collation to which at least one of the plural collation algorithms is applied, the first physical feature of the user input is normal Determine that it belongs to the user,
    Multimodal authentication device.
  2. 　前記第１の照合手段は、前記複数種類の照合アルゴリズムのうち、照合速度が速いものから順に適用し、１つの照合が成立した時点で照合動作を中止し、入力される前記認証対象者の第１の身体的特徴が正規ユーザのものであると判断する、請求項２に記載のマルチモーダル認証装置。 The first matching means is applied in order from the fastest matching speed among the plurality of types of matching algorithms, stops the matching operation at the time when one matching is established, The multimodal authentication device according to claim 2, wherein the one physical feature is determined to be that of an authorized user.
  3. 　前記認証対象者の第１および第２の身体的特徴を、同一の身体的部位から入力する入力手段をさらに備える、請求項１または２に記載のマルチモーダル認証装置。 The multimodal authentication device according to claim 1 or 2, further comprising input means for inputting the first and second physical characteristics of the person to be authenticated from the same physical part.
  4. 　前記入力手段は、前記同一の身体的部位から同一のセンサを用いて入力する、請求項３に記載のマルチモーダル認証装置。 The multimodal authentication device according to claim 3, wherein the input means inputs from the same physical part using the same sensor.
  5. 　前記第２の照合手段は、複数種類の照合アルゴリズムを適用して正規ユーザのものであるか否かの判断を行い、
    　前記第２の照合手段は、前記複数種類の照合アルゴリズムのうち、少なくともいずれか１つの照合アルゴリズムを適用した照合において照合が成立した場合に、入力される前記認証対象者の第２の身体的特徴が正規ユーザのものであると判断する、請求項１～４のいずれか１の請求項に記載のマルチモーダル認証装置。     The second collating unit determines whether the user is a legitimate user by applying a plurality of collating algorithms,
    The second verification unit is configured to input the second physical feature of the person to be authenticated that is input when verification is established in verification using at least one of the plurality of verification algorithms. The multimodal authentication device according to any one of claims 1 to 4, wherein the multi-modal authentication device determines that is an authorized user.
  6. 　入力される認証対象者の第１の身体的特徴について、複数種類の照合アルゴリズムを適用して正規ユーザのものであるか否かの判断を行う第１の照合手段と、
    　入力される前記認証対象者の第２の身体的特徴について、１種類以上の照合アルゴリズムを適用して正規ユーザのものであるか否かの判断を行う第２の照合手段と、
    　前記第１および第２の照合手段において照合が成立した場合に、前記認証対象者が正規ユーザであると判断する認証手段とを備え、
    　前記第１の照合手段は、前記複数種類の照合アルゴリズムを組み合わせ、各照合アルゴリズムを適用した場合に得られる、正規ユーザのものであるか否かを表す各理論値に重み付けを行い、重み付けした各理論値を統合した結果に基づいて照合が成立すると判断した場合に、入力される前記認証対象者の第１の身体的特徴が正規ユーザのものであると判断する、
    　マルチモーダル認証装置。     A first verification unit that determines whether or not the first physical feature of the input person to be authenticated belongs to an authorized user by applying a plurality of types of verification algorithms;
    A second verification unit that determines whether or not the second physical feature of the authentication target person is an authorized user by applying one or more verification algorithms;
    Authentication means for determining that the person to be authenticated is a regular user when the first and second matching means are matched;
    The first matching means weights each theoretical value representing whether or not a regular user is obtained by combining the plurality of types of matching algorithms and applying each matching algorithm. When it is determined that collation is established based on the result of integrating theoretical values, it is determined that the first physical feature of the authentication target person to be input is that of a regular user.
    Multimodal authentication device.
  7. 　入力される認証対象者の第１の身体的特徴について、複数種類の照合アルゴリズムを適用して正規ユーザのものであるか否かの判断を行う照合ステップであって、前記複数種類の照合アルゴリズムのうち、少なくともいずれか１つの照合アルゴリズムを適用した照合において照合が成立した場合に、入力される前記ユーザの第１の身体的特徴が正規ユーザのものであると判断する第１の照合ステップと、
    　入力される前記認証対象者の第２の身体的特徴について、１種類以上の照合アルゴリズムを適用して正規ユーザのものであるか否かの判断を行う第２の照合ステップと、
    　前記第１および第２の照合ステップにおいて照合が成立した場合に、前記認証対象者が正規ユーザであると判断する認証ステップと、
    　を含むマルチモーダル認証方法。     A verification step for determining whether or not the first physical feature of the authentication target person is an authorized user by applying a plurality of types of verification algorithms, wherein the plurality of types of verification algorithms A first collation step of determining that the first physical feature of the input user is that of a regular user when collation is established in collation using at least one of the collation algorithms;
    A second collation step for determining whether or not the second physical feature of the input person to be authenticated is that of an authorized user by applying one or more collation algorithms;
    An authentication step of determining that the person to be authenticated is a regular user when the verification is established in the first and second verification steps;
    Including multi-modal authentication methods.
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