JP2005202765A - Biometric collating device, biometric collating method, and passing controller - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a biometric collating device for enabling a collation object person to feel that collation processing has ended in a shorter period of time than the actual collating time, and for enabling the collation object person to move to a position optimal to the collation processing. <P>SOLUTION: In 1 to N collation in a biometric collating device for deciding whether or not the collation object person is a principal by using the moving image of the collation object person, when the face region of the collation object person is detected, the collation processing is started, and it is displayed that the collation processing is under way after the lapse of a predetermined time (for three frame images). <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 matching device acquires biometric information of a person registered in advance as a verification target person using a camera, a sensor, or the like, and the person-specific feature information obtained from the acquired biometric information is dictionary information. Is stored (registered) in advance in the dictionary 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 to be collated is the person himself / herself based on the obtained similarity.

  In such a biometric collation apparatus, collation mode (hereinafter referred to as 1: N collation mode) in which collation is performed with all (a plurality of) dictionary information registered in the dictionary storage unit, and collation is performed using specific information. A collation mode (hereinafter referred to as 1: 1 collation mode) for collating with dictionary information corresponding to the person after specifying the person to be collated, and collating with the person to be collated during collation Is to inform you.

  By the way, recently, a biometric matching apparatus that performs biometric matching (for example, face matching) using an input moving image has been developed. A biometric matching device that performs biometric matching using moving images, for example, using a video camera, continuously inputs a plurality of frames of a person's face image as a person to be verified, and inputs a plurality of frames that are continuously input. The person's unique facial feature information respectively obtained from the image is sequentially compared with dictionary information stored in advance in the dictionary storage means to obtain the similarity between the two information, and the person is obtained from the obtained similarity. Is to determine whether or not the person is the person.

  However, a biometric matching device that performs biometric matching using moving images is characterized in that the matching result cannot be output until the necessary number of images (for frames) are acquired, and therefore the matching time is increased. Therefore, in order to shorten the collation time, it is conceivable to shorten the acquisition interval of a plurality of images, but in such a case, a computer that can process at high speed is required, and there is little change between input images, There will be no variations in the input image, and the collation performance will be affected.

  Normally, in 1-to-N collation, the collation process is performed when a face area is detected when the person to be collated approaches from the camera as the image acquisition means from the distance or moves from the left-right direction to the center of the camera. Start. If the verification target person is informed that the verification process is started immediately after the verification process is started, the verification target person may stop at that position. In this case, the matching process is performed not on the face area suitable for the matching process but on the face area that can be detected at the last minute, which greatly affects the matching performance.

  Therefore, the present invention makes it possible for the verification target person to feel that the verification process has been completed in a time shorter than the actual verification time, and to move the verification target person to an optimal position for the verification process. 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 person to be collated, and unique feature information obtained from biometric information of a plurality of persons registered in advance as a person to be collated. Dictionary storage means for storing information, biometric information area detecting means for detecting a biometric information area of a person as the verification target person from the acquisition result of the biometric information acquisition means, and the verification target person by the biometric information area detection means When the biometric information area of the person is detected, a first control unit that controls the biometric information acquisition unit so as to continuously acquire a plurality of biometric information of the person, and the control of the first control unit A plurality of pieces of biological information obtained from the biological information acquisition unit are respectively compared with a plurality of pieces of dictionary information stored in the dictionary storage unit. The collating means for determining whether or not the person as the person to be collated is the person, and the time counting operation that starts when the biological information area of the person as the person to be collated is detected by the biological information area detecting means And a display means for displaying information indicating that the collation is currently being performed when the time counted by the timing means reaches a predetermined set value.

  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 a biometric information region of the person as the verification target person from the acquisition result of the biometric information acquisition step. A biometric information area detecting step, and when the biometric information area of the person as the verification target person is detected by the biometric information area detection step, a plurality of biometric information of the person as the verification target person is continuously acquired. A first control step to be controlled, a plurality of pieces of biometric information obtained by the control of the first control step, and unique feature information obtained from biometric information of a plurality of persons registered in advance as verification subjects By collating each of a plurality of dictionary information stored in the dictionary storage means for storing as information, the person to be collated is based on each collation result A collation step for determining whether or not the person is the person, and a clocking step for starting a clocking operation when the biometric information area of the person as the collation target person is detected by the biometric information area detection step, When the time counted by this timing step reaches a predetermined set value, a display step is provided for displaying information indicating that the current verification is being performed.

  Furthermore, the traffic control device of the present invention includes a biometric information acquisition unit that acquires biometric information of a passer-by as a person to be verified, and a unique information obtained from biometric information of a plurality of passers-by who have been registered in advance as verification persons. Dictionary storage means for storing feature information as dictionary information, biometric information area detection means for detecting a biometric information area of a passerby as the person to be collated from the acquisition result of the biometric information acquisition means, and this biometric information area detection means When the biometric information area of the passerby as the person to be collated is detected by the first control unit, the first control unit controls the biometric information acquisition unit so as to continuously acquire a plurality of the biometric information of the passerby, A plurality of pieces of biological information obtained from the biological information acquisition means by the control of one control means, respectively, by collating with a plurality of dictionary information stored in the dictionary storage means, Collation means for determining whether or not the passerby as the person to be collated is a person based on the result of collation, and traffic control for controlling the passage of the passerby as the person to be collated according to the determination result of the collation means And a time setting means for starting the time measuring operation when the biometric information area of the passerby as the person to be collated is detected by the biometric information area detecting means, and a time set by the time measuring means set in advance. When the value is reached, display means for displaying information indicating that the verification is currently being performed is provided.

  According to the present invention, it is possible to make the verification target person feel that the verification process is completed in a time shorter than the actual verification time, and to move the verification target person to an optimal position for the verification process. 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 means for detecting the position of face parts such as face, eyes and nose by collation with a dictionary, face detection section 106 as biometric information area detection means, density information or partial space information based on the output of face detection section 106, etc. The feature extraction unit 107 as a feature extraction unit that extracts the feature amount (feature information) of the face, and the facial feature amount (feature information) extracted by the feature extraction unit 107 at the time of registration of dictionary information is converted into dictionary information (recognition data). ) Is stored (registered) as dictionary storage means 108, and at the time of biometric matching (face matching), the facial feature amount (input characteristics) extracted by the feature extraction unit 107 is stored. Information) and the dictionary information stored in the dictionary information storage unit 108, thereby recognizing unit 109 as a verification unit for determining whether or not the verification target person 100 is the person based on the verification result, The control unit 110 is configured as a control unit that controls the illumination unit 102, the input / output 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 face matching processing in such a configuration 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, symbol M1 indicates the captured face image (input image) of the person 100 to be verified, and symbol P1 indicates a guidance sentence displayed for the person 100 to be verified (for example, “Please stand in front of the camera”). This example of the input image shows 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.

  For example, when the image captured by the camera 101 becomes like M2 shown in FIG. 5B and the face area can be detected in step S4, the control unit 110 counts time using a hardware timer or software timer (not shown). The operation is started (step S5) and collation processing in the 1-to-N collation mode (a mode for collating with all registered dictionary information) is started (step S6). Here, the process of step S5 corresponds to the time measuring means in the present invention.

  That is, the image input unit 105 acquires the first frame image from the camera 101, and sends the image to the face detection unit 106 (step S7). The face detection unit 106 detects a face area from the first frame image captured by the camera 101, and detects the position of a facial part 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 a maximum value is selected from the obtained similarities, and the similarity indicating the selected maximum value is temporarily stored in a memory (not shown) (step S8).

  Next, the control unit 110 checks whether or not the time measured when the time measuring operation is started in step S5 has reached a predetermined set value (step S9), and the time measured has not yet reached the set value. Returns to step S7 and repeats the same processing as described above for the next frame. Here, for example, if the frame interval for capturing an image by the camera 101 is 100 ms, the set value is set to 300 ms (time for acquiring three frame images).

  As a result of the check in step S9, when the timekeeping time reaches the set value, the control unit 110, as shown in FIG. For example, a character pattern (for example, “under collation”) P2 indicating that collation is being performed is displayed to the collation target person 100 together with the input image M3 at this time (step S10).

  Next, the control unit 110 checks whether or not image acquisition for a predetermined number of frames (for example, 13 frames if the frame interval for capturing images is 100 ms as described above) has ended ( Step S11) If not completed yet, the process returns to Step S7, and the same processing as described above is repeated for the next frame.

As a result of the check in step S11, when image acquisition for a predetermined number of frames is completed, the control unit 110 determines the maximum similarity (from the first frame image) for each frame image temporarily stored in a memory (not shown). The similarity indicating the highest value is selected from each maximum similarity (up to the 13th frame image), the person having the similarity indicating the selected highest value is determined to be the person 100 to be collated, and the determination result is output. (Step S12).
Next, the control unit 110 turns off the character pattern P2 displayed on the screen of the input / output unit 103 and indicating that the current verification is being performed (step S12), and ends the verification process.

  In the first embodiment, the case where a character pattern (for example, “during collation”) is displayed as information indicating that collation is currently being performed has been described. However, the present invention is not limited to this. For example, the display may be performed by a dedicated display or the like other than the symbols and the input / output unit 103.

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. 6 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.
In FIG. 6, the configuration other than the door control unit 112 is the same as that of the biometric matching device in FIG. 1, and thus the same reference numerals are given and description thereof is 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 embodiment, the following operational effects can be expected.
That is, in the one-to-N collation that does not involve an operation such as key input, it is not known when the collation process is started. Therefore, the collation target person recognizes that the collation is in progress only after the display indicating that collation is being performed. Therefore, even if the collation process is started, the collation process can be performed without a sense of incongruity even if the start of the collation display is delayed. As a result, the target person is not aware of the image that is actually required for the verification process, but the target person is not aware of it. It is possible to make the user feel as if the collation process has been completed in a time shorter than the collation time, thereby reducing the burden of the collation process.

  In the 1-to-N matching, the person to be matched moves from a position where no face area is detected to a position where face detection is performed, and starts the matching process. At that time, by delaying notifying the person to be collated that the collation process has been started, the person closes to the camera or moves to the center without stopping at the last position of face area detection. Thereby, it is possible to make the face region optimal for face matching, and to improve matching performance.

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 an input image and now collating. 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 part (biological information acquisition means, image input means), 106 ... face detection part (biological information area detection means, face detection means), 107 ... feature extraction part (feature extraction means), 108 ... dictionary information storage part ( Dictionary storage means), 109... Recognition section (collation means), 110... Control section (control means, timing means), 112. Door control section (traffic control means), 201.

Claims (6)

Biometric information acquisition means for acquiring biometric information of a person as a person to be verified;
Dictionary storage means for storing, as dictionary information, unique feature information obtained from biometric information of a plurality of persons registered in advance as verification subjects;
Biometric information area detection means for detecting a biometric information area of a person as the person to be collated from the acquisition result of the biometric information acquisition means;
When the biological information area of the person as the person to be collated is detected by the biological information area detection means, a first control means for controlling the biological information acquisition means to continuously acquire a plurality of biological information of the person. When,
By collating a plurality of pieces of biometric information obtained from the biometric information acquisition unit by the control of the first control unit with a plurality of dictionary information stored in the dictionary storage unit, the collation target is based on each collation result. Verification means for determining whether or not the person as the person is the person,
Timing means for starting a timing operation when the biological information area of the person as the person to be collated is detected by the biological information area detection means;
When the time measured by the time measuring means reaches a predetermined set value, display means for displaying information indicating that the current verification is being performed;
A biometric collation apparatus comprising: Image acquisition means for acquiring a face image of a person as a person to be verified;
Dictionary storage means for storing, as dictionary information, unique feature information obtained from face images of a plurality of persons registered in advance as verification targets;
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;
A first control unit that controls the image acquisition unit so as to continuously acquire a plurality of face images of the person when the face detection unit detects the face area of the person as the person to be collated;
When a face area of a person as the person to be collated is detected by the face detection means for a plurality of face images obtained from the image acquisition means by the first control means, the person is identified by image information of the face area. Feature extraction means for extracting unique feature information;
Whether or not the person as the person to be collated is the person himself / herself by collating the feature information extracted by the feature extraction unit with the plurality of dictionary information stored in the dictionary storage unit. A verification means for determining whether or not
A timing unit that starts a timing operation when a face area of the person as the person to be collated is detected by the face detection unit;
When the time measured by the time measuring means reaches a predetermined set value, display means for displaying information indicating that the current verification is being performed;
A biometric collation apparatus comprising:   3. A second control unit for stopping display of information indicating that the collating unit is currently collating by the display unit when the collating process by the collating unit is completed. Biometric verification device. A biometric information acquisition step of acquiring biometric information of a person as a person to be verified;
A biometric information area detecting step for detecting a biometric information area of the person as the person to be collated from the acquisition result of the biometric information acquiring step;
A first control step for controlling to continuously acquire a plurality of pieces of biometric information of the person as the verification target when a biometric information area of the person as the verification target is detected by the biometric information area detection step; ,
A plurality of biometric information obtained by the control of the first control step and unique feature information obtained from biometric information of a plurality of persons registered in advance as collation subjects are stored in dictionary storage means for storing as dictionary information. A collation step of determining whether or not the person as the person to be collated is the person himself / herself by collating each of the plurality of dictionary information performed,
A timing step for starting a timing operation when a biological information area of the person as the person to be collated is detected by the biological information area detection step;
When the time counted by this timing step reaches a predetermined set value, a display step for displaying information indicating that the current verification is being performed;
A biometric matching method characterized by comprising: Biometric information acquisition means for acquiring biometric information of a passerby as a person to be verified;
Dictionary storage means for storing, as dictionary information, unique feature information obtained from biometric information of a plurality of passers-by who has been registered in advance as verification subjects;
Biometric information area detection means for detecting a biometric information area of a passerby as the person to be collated from the acquisition result of the biometric information acquisition means;
When the biometric information area of the passerby as the person to be collated is detected by the biometric information area detection unit, the biometric information acquisition unit is controlled to acquire a plurality of biometric information of the passerby continuously. Control means;
By collating a plurality of pieces of biometric information obtained from the biometric information acquisition unit by the control of the first control unit with a plurality of dictionary information stored in the dictionary storage unit, the collation target is based on each collation result. A verification means for determining whether or not the passerby is a person,
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;
Timing means for starting a timing operation when the biological information area of the passerby as the person to be collated is detected by the biological information area detection means;
When the time measured by the time measuring means reaches a predetermined set value, display means for displaying information indicating that the current verification is being performed;
A traffic control device comprising:   6. The traffic control apparatus according to claim 5, further comprising second control means for stopping display of information indicating that the display means is currently being verified by the display means when the verification processing by the verification means is completed. .

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