JP2005202732A - Biometric collating device, biometric collating method, and passing controller - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a biometric collating device for notifying a collation object person that the position or size of biological information is proper, and for acquiring the biological information in state optimal for the collation, and for improving collating precision. <P>SOLUTION: This biometric collating device for deciding whether or not a figure is the principal by using a face image is configured so that when the face region of an input image is positioned and sized suitably for collation, a circular pattern in green can be displayed in the same size as the size of the face image so as to be overlapped with the face region of the input image. <P>COPYRIGHT: (C)2005,JPO&NCIPI

Description

Whether or not the person is the person using the biological information such as the face image, fingerprint image, iris information, palm image, finger image, voice information, sympathetic information, etc. The present invention relates to a biometric matching device and a biometric matching method.
The present invention also relates to a traffic control device that controls a passerby's traffic (for example, entrance / exit of an important facility) using the biometric matching device.

  In general, this type of biometric collation apparatus acquires biometric information of a person as a collation target in advance using a camera, a sensor, or the like, and uses the acquired biometric information as characteristic information unique to the person as dictionary information. It is stored (registered) in advance in the storage means.

  And at the time of collation, the biometric information of the person as a collation subject is acquired again using a camera, a sensor, etc., and the characteristic information peculiar to the person obtained from the acquired biometric information is stored (registered) in the dictionary storage means in advance. By determining the similarity between the two information by collating with the dictionary information, it is determined whether or not the person is the person based on the determined similarity.

In such a biometric matching device, as a means for fixing the position and size of the input biometric information, a method for displaying a frame for designating the size and position of the biometric information (for example, see Patent Document 1), There is a method of displaying an index for designating the size and position of biological information (for example, see Patent Document 2). These methods are characterized in that a pattern for matching the position and size of biological information is displayed in advance, and the person to be matched matches the pattern.
JP 2002-229955 A JP 2003-317100 A

  However, in the biometric matching device using biometric information, the position and size of the input biometric information changes each time collation is performed, so that collation is performed at the same position and size as when biometric information was registered. Is not limited. Further, there is a problem that the accuracy of collation is greatly affected as the input biometric information is moved away from the position and size at the time of registration.

  Therefore, the present invention can notify the person to be collated that the position and size of the biometric information has become appropriate, so that the biometric information can be acquired in an optimal state for collation, and the collation accuracy is improved. An object of the present invention is to provide a biometric matching device, a biometric matching method, and a traffic control device.

  The biometric matching device of the present invention includes a biometric information acquisition unit that acquires biometric information of a person as a verification target person, and a display that displays the biometric information acquired by the biometric information acquisition unit for the person as the verification target person. Means, dictionary storage means for storing unique feature information obtained from biometric information of a person registered in advance as a collation target person as dictionary information, biometric information acquired by the biometric information acquisition means, and dictionary storage means The collation means for collating with the dictionary information stored in the information to determine whether or not the person as the person to be collated is the person himself / herself based on the respective collation results, and the biometric information acquired by the biometric information acquisition means A determination means for determining whether at least one of the position and the size of the information has reached a predetermined value, and the determination means When it is determined that at least one of the position and size of the biometric information acquired by the biometric information acquisition means has reached a predetermined value, at least one of the position and size of the acquired biometric information Control means for controlling the display means so as to display information indicating that has reached a predetermined value together with the acquired biological information.

  Further, the biometric matching method of the present invention includes a biometric information acquisition step for acquiring biometric information of a person as a verification target person, and the biometric information acquired by the biometric information acquisition step for the person as the verification target person. Dictionary storage means for storing, as dictionary information, the first display step, the biometric information acquired by the biometric information acquisition step, and unique feature information obtained from the biometric information of a person registered in advance as a person to be collated A collation step for collating with the dictionary information stored in the database to determine whether or not the person as the person to be collated is the person based on each collation result, and the biometric information acquired by the biometric information acquisition step A determination step for determining whether at least one of the position and the size of the information has reached a predetermined value. If it is determined in this determination step that at least one of the position and size of the biological information acquired in the biological information acquisition step has reached a predetermined value, the position and size of the acquired biological information And a control step for controlling the display step so that information indicating that at least one of the values has reached a predetermined value is displayed together with the acquired biological information.

  Furthermore, the traffic control device of the present invention provides biometric information acquisition means for acquiring biometric information of a passerby as a person to be collated and biometric information acquired by the biometric information acquisition means to the passerby as the person to be collated. Display means for displaying, dictionary storage means for storing unique feature information obtained from biometric information of a passerby previously registered as a person to be verified as dictionary information, and biometric information acquired by the biometric information acquiring means And collating the dictionary information stored in the dictionary storage means to determine whether or not the passerby as the person to be collated is the person himself / herself based on the result of each collation, A passage control means for controlling the passage of the passerby as the person to be collated according to the determination result, and the position and size of the biological information acquired by the biological information acquisition means; A determination unit that determines whether or not at least one of the predetermined values has been determined in advance, and at least one of the position and the size of the biological information acquired by the biological information acquisition unit by the determination unit is When it is determined that a predetermined value has been reached, the display is performed so that information indicating that at least one of the position and size of the acquired biological information has reached a predetermined value is displayed together with the acquired biological information. Control means for controlling the means.

  ADVANTAGE OF THE INVENTION According to this invention, it can notify a collation subject that the position and magnitude | size of biometric information became suitable, and biometric information can be acquired now in the optimal state for collation, and collation precision is improved. A biometric matching device, a biometric matching method, and a traffic control device can be provided.

Hereinafter, embodiments of the present invention will be described with reference to the drawings.
In the following description, a case where a face image is used as the biological information of a person will be described as an example. However, in addition to the face image, a fingerprint image, an iris information, a palm-shaped image, a finger image, voice information, rhythm information, etc. The same can be implemented using other biological information.

  FIG. 1 schematically shows a configuration of a biometric matching apparatus according to the present embodiment. The biometric matching device includes an image acquisition unit that captures and inputs a face image (an image including at least a face) of a verification target person (hereinafter also referred to as a person) 100, and a television camera 101 as a biometric information acquisition unit. Illumination unit 102 as illumination means for irradiating light with a constant illuminance from the vicinity of the camera 101 toward at least the face of the person 100 to be collated, a face image input to the person 100 to be collated, various types of guidance, and the like are displayed. Or a display unit for inputting an ID number (specific information) or a password for identifying the person to be verified 100, a password or the like, and an input / output unit 103 as an input unit, and a face image input from the camera 101 to process the face The image processing apparatus includes a processing unit 104 that performs image recognition processing and the like.

  The camera 101 captures and inputs a face image of the person 100 to be collated from below at a predetermined angle. For example, the camera 101 includes a television camera using an image sensor such as a CCD sensor.

  The illuminating unit 102 is an illuminating device such as a fluorescent lamp that emits light at a constant illuminance from the vicinity of the camera 101 (for example, the side of the camera 101) toward the face of the person 100 to be verified.

  The input / output unit 103 displays the face image of the verification target person 100 captured by the camera 101, various guidance, processing results, and the like for the verification target person 100, and the personal ID and password of the verification target person 100. For example, the liquid crystal display unit and the touch panel are integrated, and substantially correspond to the face portion of the person 100 to be collated near the camera 101, for example, above the camera 101. In the position. Note that not only the guidance by display but also a voice guidance function may be added.

  The processing unit 104 uses an image acquisition unit that inputs a face image from the camera 101, an image input unit 105 as a biometric information acquisition unit, and a human face image obtained from the image input unit 105 to prepare a pattern prepared in advance. Face detection unit 106 serving as a face detection unit that detects the position of facial parts such as the face, eyes, and nose by collation with a dictionary, and facial features such as grayscale information or partial space information based on the output of the face detection unit 106 ( Feature extraction unit 107 as a feature extraction means for extracting feature information), and at the time of registration of dictionary information, the facial feature amount (feature information) extracted by feature extraction unit 107 is stored (registered) as dictionary information (recognition data). The dictionary information storage unit 108 serving as a dictionary storage unit for performing the biometric matching (face matching) and the facial feature amount (input feature information) extracted by the feature extraction unit 107 and the dictionary information storage unit 1 8, a recognition unit 109, a lighting unit 102, and an input / output unit as collation means for judging whether or not the collation target person 100 is the person based on the collation result by collating with the dictionary information stored in FIG. The control unit 110 is configured as control means for controlling the control unit 103 and the like.

  In the following description, image input data, extracted feature quantities (feature information), subspace, eigenvectors for constructing the subspace, correlation matrix, registration time, date / time, status information such as location, password, Each piece of personal information such as an ID number exists. And when it says recognition data, it contains the eigenvector for comprising a partial space or a partial space, and when it says dictionary information (registration information), it is image input data, the extracted feature-value, partial space, partial space. Includes an eigenvector, a correlation matrix, situation information, and personal information. Accordingly, the recognition data is included in the registration information.

The image input unit 105 inputs the face image from the camera 101, digitizes it by A / D conversion, and sends it to the face detection unit 106.
First, the face detection unit 106 detects a face area of the person 100 to be collated from the face image input by the image input unit 105. For example, by obtaining a correlation value while moving a template prepared in advance in an image, a place having the highest correlation value is set as a face region. In addition, face detection means such as a face region extraction method using an eigenspace method or a subspace method may be used.

  Next, the face detection unit 106 detects the position of the facial parts such as eyes, nose, and mouth from the detected face area. The detection method is described in, for example, literature (Kazuhiro Fukui, Osamu Yamaguchi: “Face Feature Point Extraction by Combination of Shape Extraction and Pattern Matching”, IEICE Transactions (D), vol. J80-D-II, No. 8, pp2170-2177 (1997)).

  FIG. 2 shows an example of face detection results and eye / nose detection results. In FIG. 2, (fx, fy) is the center coordinates of the face, (fw, fh) is the size of the face, (EyeLx, EyeLy), (EyeRx, EyeRy) are the position coordinates of the left and right eyes, (NoseLx, NoseLy) , (NoseRx, NoseRy) indicate the position coordinates of the left and right nostrils. The eye position indicates the center point of the black eye, and the nose position indicates the center point of the nostril.

  The feature extraction unit 107 cuts the face area into a certain size and shape based on the position of the face part detected by the face detection unit 106, and uses the shading information as a feature amount. Here, for example, the gray value of an area of m pixels × n pixels is used as information as it is, and m × n-dimensional information is used as a feature vector.

  Further, as will be described later, the partial space itself may be used as input data for recognition. Therefore, the result of calculating the partial space is sent to the recognition unit 109 and the dictionary information storage unit 108.

  The dictionary information storage unit 108 holds dictionary information such as a partial space (or correlation matrix) used for recognizing or identifying the person 100 to be verified. Also, attribute information such as date and time, time, and place at the time of registration can be held. The dictionary information is not limited to the partial space, and an input face image or an extracted face feature amount itself may be used.

  The recognizing unit 109 collates (compares) the recognition data (partial space) stored in the dictionary information storage unit 108 with the feature amount (shading information or partial space information) obtained by the feature extracting unit 107, thereby It recognizes who the person 100 to be collated who is photographing at 101 is identified, or identifies whether it is a corresponding person. In order to recognize a person, it suffices to determine which person's data is most similar, and the person corresponding to the data having the maximum similarity may be used as the recognition result.

  In addition, when performing facial recognition using a card, ID number, personal identification number, key, etc., the degree of similarity with recognition data corresponding to personal information such as each person's card or ID number is calculated. The threshold is set, and if the threshold is exceeded, the person is identified.

  Means for inputting such a card, an ID number, a personal identification number, a key, and the like are necessary. When an ID number or a password is used, key input means may be provided.

  As a recognition method, when information of the feature extraction unit 107 is used, a method such as a subspace method or a composite similarity method may be used. The recognition method in the present embodiment is, for example, a literature (Kenichi Maeda, Sadaichi Watanabe: “Pattern matching method introducing a local structure”, IEICE Transactions (D), vol. J68-D, No. 3, pp 345-352 (1985)), a mutual subspace method which is a known recognition method is used.

In this method, both the recognition data in the registration information stored in advance and the input data are expressed as partial spaces, and the “angle” formed by the two partial spaces is defined as the similarity. The subspace input here is referred to as an input subspace. Similarly, a correlation matrix Cin is obtained for the input data string,

And the eigenvector Φin is obtained. The subspace similarity (0.0 to 1.0) of the subspace represented by two Φin and Φd is obtained and used as the similarity for recognizing it.

  The recognition unit 109 operates as in the flowchart shown in FIG. First, the operation varies depending on whether recognition processing (one-to-one matching) or identification processing (one-to-one matching) is performed (step ST1). When performing the identification process, first, the ID number of the target person to be collated is read (step ST2). Next, registration information (dictionary information) corresponding to the target ID number is read from the dictionary information storage unit 108 (step ST3).

  Next, as described above, in order to perform recognition by the subspace method or the like, the similarity between the subspace of each registered information and the input vector (eigenvector from the feature extraction unit 107) or the input subspace is calculated. (Step ST4). Next, the similarity is compared with a preset threshold value (steps ST5 and ST6), and the identification result is output (step ST7).

  When performing recognition processing, all dictionary information to be collated is read from the dictionary information storage unit 108 (step ST8). Then, the similarity with each dictionary information is calculated (step ST9). Next, the maximum similarity is selected from the calculated similarities (step ST10), and is output as a recognition result (step ST12).

  Note that it is also possible to verify whether the recognition result is correct by determining the maximum similarity as a threshold value as in step ST11 surrounded by a broken line in FIG. 3 (step ST13). For example, when the degree of similarity is too low, it can be determined that it is not any recognition target.

  Next, the flow of the face matching process centered on the display process that reveals that the input image has become a position and size suitable for face matching will be described with reference to the flowchart shown in FIG.

  Now, assuming that the verification target person 100 comes toward the present apparatus (camera 101), the camera 101 captures the face image of the verification target person 100 (step S1), and the face detection unit 106 via the image input unit 105. And to the control unit 110. The control unit 110 displays the captured image on the input / output unit 103 (step S2). An example of the display image at this time is shown in FIG. In the figure, reference sign M1 represents the face image (input image) of the verification target person 100, and this example indicates that the verification target person 100 is still far from the camera 101.

  The face detection unit 106 performs a process of detecting a face area from the image captured by the camera 101 (step S3). Next, it is checked whether or not the face area can be detected (step S4). If the face area cannot be detected, the process returns to step S1 to capture the face image again and repeat the same processing as described above.

If the face area is detected as a result of the check in step S4, the control unit 110 determines whether the position and size of the face area has reached a predetermined value, for example, a position and size suitable for face matching. It is determined whether or not (step S5).
In this case, it is not always necessary to determine whether or not both the position and size of the face area have values suitable for face matching, and at least one of the position and size is predetermined. What is necessary is just to determine whether it became a value.

  As a result of the check in step S5, if the position and size of the detected face area are not values suitable for face matching, the control unit 110 returns to step S1 to capture the face image again, and performs the same processing as above. repeat. Here, the processing in step S5 corresponds to the determination means and the first control means in the present invention.

For example, when the image captured by the camera 101 becomes like M2 shown in FIG. 5B, and the position and size of the detected face area become values suitable for face matching in step S5, control is performed. 5C, the position and size of the detected face area in the screen of the input / output unit 103 displaying the input image M3 from the camera 101 are suitable for face matching, as shown in FIG. In this example, a green circular pattern (annular pattern) P1 having the same size as the detected face area is superimposed on the face area of the input image M3 at this time. Displayed (step S6). Here, the process of step S6 corresponds to the second control means in the present invention.
As shown in FIG. 5 (c), a character pattern (during collation) P2 indicating that collation is being performed is also displayed at the same time.

  Next, the control unit 110 checks whether or not the collation mode is a 1-to-N collation mode (a mode for collating with all registered dictionary information) (step S7). Is started when the circular pattern P1 is displayed (steps S8 and S9).

  That is, the camera 101 captures the image of the person 100 to be verified and sends it to the face detection unit 106 via the image input unit 105. The face detection unit 106 detects a face area from the image captured by the camera 101, and detects the positions of face parts such as eyes, nose, and mouth from the detected face area.

  Next, the feature extraction unit 107 extracts a facial feature amount based on the position of the face part detected by the face detection unit 106 and sends it to the recognition unit 109. The recognizing unit 109 obtains each similarity degree of both pieces of information by collating the feature amount (feature information) of the face extracted by the feature extracting unit 107 with all the dictionary information in the dictionary information storage unit 108. A similarity indicating the maximum value is selected from the obtained similarities, and the person having the similarity indicating the selected maximum value is determined to be the person 100 to be collated. Here, the process of step S8 corresponds to the third control means in the present invention.

  If the result of the check in step S7 is not the one-to-N collation mode, the control unit 110 determines that the collation mode is the one-to-one collation mode (a mode for collating with dictionary information of a person specified in advance). It is checked whether or not the input of the ID number by the person 100 has been completed. If the input of the ID number has not been completed, the system waits for the ID number to be input (step S10).

  In step S10, when the input of the ID number is completed, the collation process is started (steps S11 and S12). That is, the camera 101 captures the image of the person 100 to be verified and sends it to the face detection unit 106 via the image input unit 105. The face detection unit 106 detects a face area from the image captured by the camera 101, and detects the positions of face parts such as eyes, nose, and mouth from the detected face area.

  Next, the feature extraction unit 107 extracts a facial feature amount based on the position of the face part detected by the face detection unit 106 and sends it to the recognition unit 109. The recognizing unit 109 collates the facial feature amount extracted by the feature extracting unit 107 with the dictionary information corresponding to the ID number of the person 100 to be collated previously input in the dictionary information storage unit 108 to thereby obtain both information. If the obtained similarity is higher than the threshold, it is determined that the person to be collated 100 is a registrant (person), and if the obtained similarity is lower than the threshold, an unregistered person It is determined that it is not the person.

  In the first embodiment, the detected face area displayed on the screen of the input / output unit 103 when the position and size of the detected face area are suitable for face matching. As information indicating that the position and size have become values suitable for face matching, a green circular pattern (annular pattern) P1 having the same size as the size of the detected face region is used as the input image M3 at this time. However, the present invention is not limited to this. For example, as shown in FIG. 6, the size of the detected face region is the same as that of the detected face region. A rectangular pattern (annular pattern) P3 may be displayed superimposed on the face area of the input image M3 at this time. For example, as shown in FIG. 7A, a green circular pattern P1 is displayed. , Detected face area size Is displayed in a position different from the face area of the input image M3 at this time, or, for example, as shown in FIG. 7B, a green rectangular pattern P3 is displayed on the detected face. The size may be different from the size of the area, and may be displayed at a position different from the face area of the input image M3 at this time.

Further, for example, as shown in FIG. 8, a circular pattern P4 is displayed when the position of the detected face area becomes a value suitable for face matching, and the size of the detected face area is suitable for face matching. The rectangular pattern P5 may be displayed when the value is reached.
In addition, a circular pattern such as a circle or a rectangle may be displayed, for example, as a character pattern (“OK” is displayed when the position of the detected face area becomes a value suitable for face matching, “OK” is displayed when the size of the detected face area becomes a value suitable for face collation).
Further, for example, a specific symbol or the like may be displayed in advance, and the symbol or the like may be blinked when the position and size of the detected face area become values suitable for face matching.

Next, a second embodiment will be described.
The second embodiment is an example in which the biometric matching device described in the first embodiment is applied to a traffic control device that recognizes a passer's face image and controls the traffic of the passer.

FIG. 9 schematically shows the configuration of the traffic control device according to the second embodiment. This traffic control device, for example, manages entry / exit to important facilities (such as security-oriented rooms), recognizes the face image of the user (passerby), and enters the important facility based on the recognition result. Open / close control of the exit door is performed, and the entrance / exit door 202 of the important facility 201 is opened / closed according to the recognition results of the camera 101, the illumination unit 102, the input / output unit 103, the processing unit 104, and the recognition unit 109. The door control unit 112 is configured as a traffic control means for performing control.
9, since it is the same structure as the biometric collation apparatus of FIG. 1 except the door control part 112, the same code | symbol is attached | subjected and the description is abbreviate | omitted.

When the recognition unit 109 determines that the verification target person 100 is the person himself / herself, the recognition unit 109 outputs a “door open” signal to the door control unit 112. When the recognition unit 109 determines that the verification target person 100 is not the person himself / herself, Outputs “door closed” signal.
When the door control unit 112 receives the “door open” signal from the recognition unit 109, the door control unit 112 controls the entrance / exit door 202 to be in an open state, and allows the verification target person (passer in this case) 100 to enter the room. When the “door closed” signal is received, the entrance / exit door 202 is kept closed, and the passer-by 100 is refused to enter the room.
As described above, according to the second embodiment, it is possible to control the passage of passers-by using the biometric matching device described in the first embodiment.

  As described above, according to the above-described embodiment, in the biometric matching apparatus that determines whether or not the person is the person using the face image, the face area of the input image is suitable for matching and size. The position and size of the face image become appropriate by displaying a green circular pattern with the same size as the face area on the face area of the input image at this time. This makes it possible to notify the person to be collated, so that a face image can be acquired in an optimal state for collation, and collation accuracy can be improved.

1 is a block diagram schematically showing a configuration of a biometric matching device according to a first embodiment of the present invention. The figure for demonstrating the process of a face detection part. The flowchart for demonstrating the flow of a process of a recognition part. The flowchart for demonstrating the flow of a face collation process. The figure which shows the example of a display of the information which shows that the position and the magnitude | size of the detected face area with respect to the said input image became the value suitable for face collation. The figure which shows the other example of a display of the information which shows that the position and magnitude | size of the detected face area became a value suitable for face collation. The figure which shows the further another example of a display of the information which shows that the position and magnitude | size of the detected face area became a value suitable for face collation. The figure which shows the further another example of a display of the information which shows that the position and magnitude | size of the detected face area became a value suitable for face collation. The block diagram which shows schematically the structure of the traffic control apparatus which concerns on the 2nd Embodiment of this invention.

Explanation of symbols

  DESCRIPTION OF SYMBOLS 100 ... Person to be verified (person, passerby), 101 ... Camera (biological information acquisition means, image input means), 102 ... Illumination section, 103 ... Input / output section (input means, display means), 104 ... Processing section, 105 ... Image input unit (biological information acquisition unit, image input unit) 106. Face detection unit (face detection unit) 107. Feature extraction unit (feature extraction unit) 108. Dictionary information storage unit (dictionary storage unit) 109 ... recognition unit (collation unit), 110 ... control unit (determination unit, control unit), 112 ... door control unit (traffic control unit), 201 ... important facility, 202 ... door for entry / exit.

Claims (8)

Biometric information acquisition means for acquiring biometric information of a person as a person to be verified;
Display means for displaying the biometric information acquired by the biometric information acquisition means for the person as the person to be collated;
Dictionary storage means for storing, as dictionary information, unique feature information obtained from biometric information of a person registered in advance as a verification target;
By comparing the biometric information acquired by the biometric information acquisition means with the dictionary information stored in the dictionary storage means, it is determined whether or not the person as the verification target person is the person based on the result of each verification. A verification means for determining;
Determination means for determining whether at least one of the position and the size of the biological information acquired by the biological information acquisition means has reached a predetermined value;
When it is determined by this determination means that at least one of the position and size of the biological information acquired by the biological information acquisition means has reached a predetermined value, the position and size of the acquired biological information Control means for controlling the display means to display information indicating that at least one of the values has reached a predetermined value together with the acquired biological information;
A biometric collation apparatus comprising:   The information indicating that at least one of the position and the size of the acquired biological information has reached a predetermined value is a predetermined circular pattern of a specific color. Biometric verification device.   2. The information indicating that at least one of the position and the size of the acquired biological information is a predetermined value is a character pattern of a specific color determined in advance. Biometric verification device.   The second control means superimposes and displays information indicating that at least one of the position and size of the acquired biological information has reached a predetermined value on the acquired biological information. The biometric matching device according to any one of claims 1 to 3, wherein the display means is controlled.   The collation unit starts a collation operation when it is determined by the determination unit that at least one of the position and the size of the biometric information acquired by the biometric information acquisition unit has reached a predetermined value. The biometric matching device according to claim 1. Image acquisition means for acquiring a face image of a person as a person to be verified;
Display means for displaying the face image acquired by the image acquisition means to the person as the person to be collated;
Dictionary storage means for storing, as dictionary information, unique feature information obtained from a face image of a person registered in advance as a verification target;
Face detection means for detecting a face area of a person as the person to be collated from the image acquired by the image acquisition means;
When the face area of the person as the person to be collated is detected by the face detection means, it is determined whether or not at least one of the position and size of the face area has reached a predetermined value. A determination means;
When it is determined by this determination means that at least one of the detected position and size of the face area does not reach a predetermined value, control is performed so that the face acquisition by the image acquisition means is performed again. Control means;
If it is determined by the determining means that at least one of the position and size of the detected face area has reached a predetermined value, at least one of the position and size of the detected face area is Second control means for controlling the display means to display an annular pattern indicating that the predetermined value has been reached together with the acquired face image;
If the determination means determines that at least one of the position and size of the detected face region has reached a predetermined value, the image acquisition is performed so that the face image of the person as the person to be collated is acquired again. Third control means for controlling the means;
When a face area of the person as the person to be collated is detected by the face detection means with respect to the image obtained from the image acquisition means by the control of the third control means, the person-specific information is obtained from the image information of the face area. Feature extraction means for extracting feature information of
By comparing the feature information extracted by the feature extraction means with the dictionary information stored in the dictionary storage means, it is determined whether or not the person as the person to be verified is the person himself / herself based on the result of each comparison Matching means to
A biometric collation apparatus comprising: A biometric information acquisition step of acquiring biometric information of a person as a person to be verified;
A first display step for displaying the biometric information acquired in this biometric information acquisition step for the person as the person to be collated;
Biometric information acquired by the biometric information acquisition step and dictionary information stored in a dictionary storage unit that stores unique feature information obtained from biometric information of a person registered as a person to be collated in advance as dictionary information. A collation step of determining whether or not the person as the person to be collated is the person himself / herself based on the collation result by collating;
A determination step of determining whether or not at least one of the position and the size of the biological information acquired by the biological information acquisition step has reached a predetermined value;
When it is determined that at least one of the position and size of the biological information acquired in the biological information acquisition step has reached a predetermined value by this determination step, out of the position and size of the acquired biological information A control step for controlling the display step to display information indicating that at least one of the values has reached a predetermined value together with the acquired biological information;
A biometric matching method characterized by comprising: Biometric information acquisition means for acquiring biometric information of a passerby as a person to be verified;
Display means for displaying the biometric information acquired by the biometric information acquisition means for a passerby as the person to be collated;
Dictionary storage means for storing, as dictionary information, unique feature information obtained from biometric information of a passerby registered in advance as a verification target;
Whether or not the passerby as the person to be collated is the person himself / herself by collating the biometric information acquired by the biometric information acquisition means with the dictionary information stored in the dictionary storage means, based on the result of each collation Verification means for determining
A passage control means for controlling the passage of the passerby as the person to be collated according to the determination result of the matching means;
Determination means for determining whether at least one of the position and the size of the biological information acquired by the biological information acquisition means has reached a predetermined value;
When it is determined by this determination means that at least one of the position and size of the biological information acquired by the biological information acquisition means has reached a predetermined value, the position and size of the acquired biological information Control means for controlling the display means to display information indicating that at least one of the values has reached a predetermined value together with the acquired biological information;
A traffic control device comprising:

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