JP2012208687A - Biological information acquisition device, biological information acquisition method and biological information acquisition program - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a biological information acquisition device, a biological information acquisition method and a biological information acquisition program capable of improving accuracy of both fingerprint information acquisition as well as vein information acquisition.SOLUTION: A biological information acquisition device comprises: a fingerprint sensor to read a fingerprint from a hand of a user; a vein sensor to read a vein from the hand of the user; and an angle evaluation section to evaluate an inclination angle of a reading surface of the fingerprint sensor with respect to the reading surface of the vein sensor. The other biological information acquisition device has: the fingerprint sensor to read the fingerprint from the hand of the user; and the vein sensor to read the vein from the hand of the user. In the other biological information acquisition device, the inclination angle of the reading surface of the fingerprint sensor with respect to the reading surface of the vein sensor is larger than 0°.

Description

  The present invention relates to a biological information acquisition device, a biological information acquisition method, and a biological information acquisition program.

  In biometric authentication that uses biometric information for personal authentication, there is a problem of reducing the probability of failure to authenticate an individual (person rejection rate) and the probability of erroneously authenticating another person (acceptance rate of others). . One means for solving this problem is “multi-biometric authentication” in which authentication is performed using a plurality of types of biometric information acquired from a plurality of parts. For example, higher authentication accuracy can be obtained by combining fingerprint authentication and palm vein authentication.

  Regarding multi-biometric authentication, Patent Literature 1 and Patent Literature 2 disclose multi-biometric authentication devices using fingerprints and veins.

JP 2003-263640 A JP 2003-303178 A

  The fingerprint information acquisition accuracy of the fingerprint sensor increases when the finger is pressed against the reading surface with a predetermined force. Therefore, it is preferable that the hand has a predetermined force. On the other hand, the vein information acquisition accuracy of the palm vein sensor increases when the palm blood flow is good. Therefore, in palm vein authentication, it is preferable that the hand has no force. From the above, there is a trade-off relationship between fingerprint information acquisition accuracy and vein information acquisition accuracy.

  The present invention has been made in view of the above problems, and an object thereof is to provide a biometric acquisition device, a biometric acquisition method, and a biometric acquisition program capable of improving both fingerprint information acquisition accuracy and vein information acquisition accuracy. To do.

  In order to solve the above problems, a biometric information acquisition device disclosed in the specification includes a fingerprint sensor that reads a fingerprint from a user's hand, a vein sensor that reads a vein from the user's hand, and reading the fingerprint sensor with respect to a reading surface of the vein sensor. And an angle evaluation unit that evaluates the inclination angle of the surface.

  In order to solve the above problems, another biometric information acquisition device disclosed in the specification includes a fingerprint sensor that reads a fingerprint from a user's hand and a vein sensor that reads a vein from the user's hand, and reads the vein sensor. The inclination angle of the reading surface of the fingerprint sensor with respect to the surface is larger than 0 °.

  In order to solve the above-described problem, the biometric acquisition method disclosed in the specification uses a fingerprint sensor to read a fingerprint from a user's hand and a vein sensor to read a vein from the user's hand. And an evaluation step for evaluating the inclination angle of the reading surface of the fingerprint sensor with respect to.

  In order to solve the above-described problem, the biometric information acquisition program disclosed in the specification uses a fingerprint sensor to read a fingerprint from a user's hand, and a vein sensor to read a palm vein from the user's hand. An evaluation step for evaluating an inclination angle of the reading surface of the fingerprint sensor with respect to the reading surface of the vein sensor is executed.

  According to the biometric acquisition device, the biometric acquisition method, and the biometric acquisition program disclosed in the specification, both fingerprint information acquisition accuracy and vein information acquisition accuracy can be improved.

1 is a block diagram for explaining a hardware configuration of a biological information acquisition apparatus 100 according to Embodiment 1. FIG. (A) And (b) is a figure for demonstrating the detail of a fingerprint sensor and a vein sensor. (A)-(c) is a figure for demonstrating the guide for arrange | positioning a user's finger | toe and the guide for arrange | positioning a user's wrist. (A)-(c) is a figure for demonstrating the inclination angle of the reading surface of a fingerprint sensor with respect to the reading surface of a vein sensor. It is a figure for demonstrating the slope by which a fingerprint sensor is arrange | positioned. It is a block diagram of each function implement | achieved by execution of a biometric information acquisition program. (A) is a figure for demonstrating an example of the flowchart performed in the case of a biometric data registration process, (b) is a figure for demonstrating the fingerprint information and vein information which were registered into the registration database. It is a figure for demonstrating an example of the flowchart performed in the case of a biometrics authentication process. It is a block diagram of each function implement | achieved by execution of the biometric information acquisition program which concerns on Example 3. FIG. It is a block diagram of each function implement | achieved in the case of an angle evaluation process. It is a figure for demonstrating an example of the flowchart performed in the case of an angle evaluation process. (A)-(d) is a figure for demonstrating a fingerprint image. It is a figure for demonstrating the time change of the contrast value C. FIG. It is a figure for demonstrating the comprehensive evaluation of angle (theta). It is an example of the flowchart for evaluating the validity of angle (theta). It is a figure for demonstrating the structure which makes angle (theta) variable. It is a block diagram of each function implement | achieved by execution of the biometric information acquisition program which concerns on Example 3. FIG. It is a figure for demonstrating an example of the flowchart performed in the case of an angle adjustment process. FIG. 10 is a block diagram for explaining a hardware configuration according to a fourth embodiment.

  Hereinafter, embodiments will be described with reference to the drawings.

  FIG. 1 is a block diagram for explaining a hardware configuration of the biological information acquisition apparatus 100 according to the first embodiment. Referring to FIG. 1, a biological information acquisition apparatus 100 includes a CPU 101, a RAM 102, a storage device 103, a fingerprint sensor 104, a vein sensor 105, a display device 106, and the like. Each of these devices is connected by a bus or the like.

  A CPU (Central Processing Unit) 101 is a central processing unit. The CPU 101 includes one or more cores. A RAM (Random Access Memory) 102 is a volatile memory that temporarily stores programs executed by the CPU 101, data processed by the CPU 101, and the like.

  The storage device 103 is a nonvolatile storage device. As the storage device 103, for example, a ROM (Read Only Memory), a solid state drive (SSD) such as a flash memory, a hard disk driven by a hard disk drive, or the like can be used. The storage device 103 stores a biological information acquisition program.

  The fingerprint sensor 104 is a sensor that acquires a fingerprint of one or more fingers placed in contact with the reading surface. The fingerprint sensor 104 is an optical sensor that acquires a fingerprint using light, and uses a difference in capacitance. For example, a capacitance sensor for acquiring a fingerprint. The fingerprint sensor 104 includes, for example, a light and a camera. The vein sensor 105 is a sensor that acquires a palm vein in a non-contact manner. For example, the vein sensor 105 photographs the subcutaneous vein of the palm using near infrared rays that are highly permeable to the human body. The vein sensor 105 includes, for example, a CMOS (Complementary Metal Oxide Semiconductor) camera. Moreover, the illumination etc. which irradiate the light containing a near infrared ray may be provided. The vein sensor 105 may include a distance sensor for acquiring the distance between the vein sensor 105 and the subject and the inclination of the subject. The display device 106 is a device for displaying the result of each process performed by the biological information acquisition device 100. The display device 106 is, for example, a liquid crystal display.

  2A and 2B are diagrams for explaining details of the fingerprint sensor 104 and the vein sensor 105. FIG. Fingerprint sensor 104 and vein sensor 105 are arranged at positions close to each other. Thereby, the fingerprint sensor 104 acquires fingerprint information of one or more fingers of the left or right hand of the user. The vein sensor 105 acquires vein information from the palm of the same hand.

  By using both fingerprint information and vein information, higher authentication accuracy can be obtained. Here, for example, if an attempt is made to simultaneously authenticate a part at a distance such as a face and a fingerprint, the apparatus will inevitably become large. Further, since the user needs to present both the face and the finger to the apparatus at the same time, the user is very restrained. On the other hand, in the combination of fingerprint information and palm vein information, two physically close features can be used for authentication. As a result, the apparatus can be made smaller than other combinations of features, and the restraint on the user can be reduced. In addition, there is an advantage that it is only necessary to hold the hand over the device.

  In addition, for impersonation, it is necessary to obtain both of them (fingerprint and vein) illegally at the same time, and to make the sensor read them correctly. However, in general, combining two features is more difficult than using a single feature. Therefore, there is an advantage that resistance to fraud such as impersonation is improved by using a combination of two types of features. Details of the fingerprint sensor 104 and the vein sensor 105 will be described below.

  Referring to FIG. 2A, since the fingerprint is normally read in contact and the vein is read in a non-contact manner, the reading surface of the fingerprint sensor 104 is arranged at a higher position than the reading surface of the vein sensor 105. Thereby, the user can bring the fingerprint into contact with the reading surface of the fingerprint sensor 104 and separate the palm from the reading surface of the vein sensor 105. For example, a preferable distance between the reading surface of the vein sensor 105 and the palm is about 5 cm ± 1 cm, but this distance varies depending on the lens or the like.

  With reference to FIG.2 (b), in the present Example, the reading surface of the fingerprint sensor 104 has the magnitude | size which can acquire the fingerprint image of an index finger, a middle finger, and a ring finger. In addition, a guide 107 for placing the thumb and little finger is provided. The guide 107 is provided so as to sandwich the fingerprint sensor 104. By placing the thumb and the little finger on the guide 107, the user can easily place the index finger, the middle finger, and the ring finger on the reading surface of the fingerprint sensor 104.

  FIG. 3A to FIG. 3C are diagrams for explaining a guide 108 for placing the user's finger and a guide 109 for placing the user's wrist. FIG. 3B is a cross-sectional view taken along line AA in FIG. FIG. 3C is a cross-sectional view taken along line BB in FIG. With reference to FIG.3 (b), the recessed part for arrange | positioning a specific finger may be provided in the guide 108. FIG. In this embodiment, the guide 108 is provided with a recess for placing the index finger, middle finger, and ring finger. With reference to FIG.3 (c), the guide 109 may be provided with the recessed part for arrange | positioning a wrist. One of the guide 108 and the guide 109 may be provided.

  As described above, by providing the guide, fingerprint information can be stably acquired by the fingerprint sensor 104, and palm vein information can be stably acquired by the vein sensor 105. Therefore, the reproducibility of the acquired fingerprint information and palm vein information is enhanced.

  Here, characteristics of the fingerprint sensor 104 and the vein sensor 105 will be described. Since the fingerprint sensor 104 is a contact-type biosensor, the fingerprint information acquisition accuracy of the fingerprint sensor 104 increases when the finger is pressed against the reading surface with a predetermined force. In particular, in order to read fingerprint information of a plurality of fingers, it is preferable to press each finger against the reading surface of the fingerprint sensor 104 with a greater force than in the case of one finger. Therefore, in order to improve fingerprint information acquisition accuracy, it is preferable that a predetermined force is in the hand. On the other hand, in order to obtain palm vein information with high accuracy, it is preferable that the blood flow in the palm is good. Therefore, in order to acquire the palm vein information with high accuracy, it is preferable that the hand is as hard as possible because deformation due to the force is less likely to occur. From the above, there is a trade-off relationship between fingerprint information acquisition accuracy and vein information acquisition accuracy.

  For example, referring to FIG. 4A, when the reading surface of the fingerprint sensor 104 and the reading surface of the vein sensor 105 are parallel, if a finger is pressed against the fingerprint sensor 104, a force is applied to the hand. . Thereby, there is a possibility that the vein acquisition accuracy by the vein sensor 105 is lowered.

  Here, the reading surface is a surface on which the target feature should exist. In the case of the fingerprint sensor 104, since it is a contact type, the reading surface coincides with a sensor surface on which a user touches a finger to read a fingerprint. On the other hand, the reading surface of the vein sensor 105 that reads a feature in a non-contact manner is a surface on which the palm of the user should be positioned with respect to the vein sensor 105. Specifically, the reading surface of the vein sensor 105 is a surface of a predetermined size that faces the camera and is present at a predetermined distance from the vein sensor 105 in the vertical direction.

  Therefore, in this embodiment, with reference to FIG. 4B, the inclination angle (hereinafter referred to as angle θ) of the reading surface of the fingerprint sensor 104 with respect to the reading surface of the vein sensor 105 is set larger than 0 °. . For example, when the reading surface of the vein sensor 105 is horizontally arranged, the reading surface of the fingerprint sensor 104 is inclined from the horizontal direction. In this case, the fingertip is naturally pressed against the reading surface of the fingerprint sensor 104 using the force of the finger. Thereby, a fingerprint can be taken without applying a great force to the hand. As a result, fingerprint information acquisition accuracy is improved. In addition, since the blood flow reduction in the palm is suppressed, the vein information acquisition accuracy is improved. Thus, by making the angle θ larger than 0 °, both the fingerprint information acquisition accuracy and the vein information acquisition accuracy can be improved.

  With reference to FIG. 5A, the fingerprint sensor 104 can be tilted by providing a slope for installing the fingerprint sensor 104 obliquely in a guide surrounding the vein sensor 105. The inclination angle of the slope from the horizontal is not particularly limited, but may be set to an angle of about 5 ° as an example.

  For example, the target users are limited in entrance / exit management. For example, when considering the management of a company's server room, the persons permitted to enter the room are determined in advance. On the other hand, for example, when comparing a man and a woman, a woman's finger is often soft, and the angle φ shown in FIG. 5B tends to be large. Therefore, when the majority of persons permitted to enter the room are known to be male (or female), it is possible to improve usability and authentication accuracy by setting the angle θ in advance. Note that the angle φ is a finger warping angle.

  Then, each process of the biometric information acquisition apparatus 100 is demonstrated. Referring to FIG. 1 again, the biometric information acquisition program stored in the storage device 103 of the biometric information acquisition apparatus 100 is developed in the RAM 102 so as to be executable. The CPU 101 executes a biometric information acquisition program developed in the RAM 102. Thereby, each process by the biometric information acquisition apparatus 100 is performed.

  FIG. 6 is a block diagram of each function realized by executing the biometric information acquisition program. With reference to FIG. 6, overall control unit 10, fingerprint acquisition unit 20, vein acquisition unit 30, authentication control unit 40, fingerprint verification unit 50, and vein verification unit 60 are realized by executing the biometric information acquisition program. The registration database is stored in the storage device 103.

  The overall control unit 10 controls the fingerprint acquisition unit 20, the vein acquisition unit 30, and the authentication control unit 40. The authentication control unit 40 controls the fingerprint collation unit 50 and the vein collation unit 60. The fingerprint acquisition unit 20 acquires fingerprint information from the fingerprint sensor 104 in accordance with an instruction from the authentication control unit 40. The vein acquisition unit 30 acquires palm vein information from the vein sensor 105 in accordance with an instruction from the authentication control unit 40.

(Biometric data registration process)
FIG. 7A is a diagram for explaining an example of a flowchart executed in the biometric data registration process for registering the fingerprint information and palm vein information of a new user in the registration database. The authentication control unit 40 starts a biometric data registration process in accordance with an instruction from the overall control unit 10. In accordance with an instruction from the authentication control unit 40, the fingerprint acquisition unit 20 acquires fingerprint information from the user's hand from the fingerprint sensor 104, and the vein acquisition unit 30 acquires palm vein information from the same hand from the vein sensor 105 (step S1). . Next, the authentication control unit 40 registers the fingerprint information and vein information acquired in step S1 in the registration database in association with the user ID and the like (step S2). Thereby, the biometric data registration process is completed.

  FIG. 7B is a diagram for explaining fingerprint information and vein information registered in the registration database. With reference to FIG. 7B, fingerprint information and vein information of a plurality of users may be registered, or fingerprint information and vein information of one user may be registered.

(Biometric authentication process)
The biometric information processing apparatus 100 executes biometric authentication processing in response to a user authentication request. FIG. 8 is a diagram for explaining an example of a flowchart executed in the biometric authentication process. 7A, the fingerprint obtaining unit 20 obtains fingerprint information of the user's hand from the fingerprint sensor 104, and the vein obtaining unit 30 obtains vein information of the palm of the same hand from the vein sensor 105. Obtain (step S11).

  Next, in accordance with an instruction from the authentication control unit 40, the fingerprint collation unit 50 performs fingerprint collation, and the vein collation unit 60 performs vein collation (step S12). Specifically, the fingerprint collation unit 50 calculates the similarity between the fingerprint information acquired in step S11 and each fingerprint information in the registration database. The vein verification unit 60 calculates the similarity between the vein information acquired in step S11 and each vein information in the registration database. The similarity of fingerprint information can be calculated based on, for example, a fingerprint image pattern, a positional relationship between fingerprint minutiae, and the like. The similarity of vein information can be calculated based on a palm vein image pattern or the like.

  Next, the authentication control unit 40 determines whether or not the highest similarity obtained by the collation in step S12 is equal to or greater than a predetermined threshold value (step S13). If it is determined as “Yes” in step S13, the authentication control unit 40 specifies that the user to be authenticated is the user having the highest similarity obtained in step S12, and outputs the identification result (step S14). When it determines with "No" in step S13, the authentication control part 40 outputs the result of an authentication failure (step S13). After execution of step S13 or step S14, execution of the flowchart ends.

  In the flowchart of FIG. 8, 1: N authentication is targeted, but 1: 1 authentication may be targeted. In this case, if the verification score obtained in step S17 is greater than or equal to the threshold value, it can be determined that the user to be authenticated is a user of registered data.

  The 1: 1 authentication is a method of performing authentication after clearly indicating who the person is using an ID card or the like in advance. On the other hand, 1: N authentication is a method of performing identification processing with data of a plurality of registered users without an ID card or the like to determine who the person is. In general, in 1: N authentication, as the number N of registered data increases, the acceptance rate of others increases stochastically. Therefore, in order to perform large-scale 1: N authentication, a method with higher authentication accuracy is required.

  If large-scale 1: N authentication can be realized, it can be used in many situations. For example, application such as realization of entrance / exit management without an ID card or the like and reliable personal authentication in immigration control can be considered. In some countries, there is no “family register” for each individual. In such a country, the name and address of an individual may be unclear, and there is a problem that it is difficult to perform personal authentication when receiving social security or welfare. In such a situation, if an individual can be authenticated without an ID, a more detailed service can be provided. In addition, by using it for confirmation at the medical site, it is possible to prevent medication and treatment errors and realize safer medical services.

  According to the present embodiment, both the fingerprint acquisition accuracy and the palm vein acquisition accuracy can be improved by making the inclination angle of the reading surface of the fingerprint sensor 104 with respect to the reading surface of the vein sensor 105 larger than 0 °. . Accordingly, high authentication accuracy can be obtained in both 1: 1 authentication and 1: N authentication.

  In the second embodiment, an example of evaluating whether the angle θ is appropriate will be described. FIG. 9 is a block diagram of each function realized by executing the biometric information acquisition program according to the third embodiment. Referring to FIG. 9, by executing the biometric information acquisition program, overall control unit 10, fingerprint acquisition unit 20, vein acquisition unit 30, authentication control unit 40, fingerprint verification unit 50, vein verification unit 60, and angle evaluation unit 70. Is realized. The registration database is stored in the storage device 103.

(Angle evaluation processing)
FIG. 10 is a block diagram of each function realized in the angle evaluation process. The angle evaluation process is executed by being incorporated in at least one of the biometric registration process and the biometric authentication process. In the angle evaluation process, the angle evaluation unit 70 functions as a fingerprint evaluation unit 71, a vein evaluation unit 72, and an angle comprehensive evaluation unit 73. FIG. 11 is a diagram for explaining an example of a flowchart executed in the angle evaluation process. Hereinafter, an example of the angle evaluation process will be described with reference to FIGS. 10 and 11. The angle evaluation process is a process for evaluating whether the angle θ is appropriate.

  First, in accordance with an instruction from the authentication control unit 40, the fingerprint acquisition unit 20 acquires fingerprint information of the user's hand from the fingerprint sensor 104, and the vein acquisition unit 30 acquires vein information of the palm of the same hand from the vein sensor 105 (step S21). Next, the fingerprint evaluation unit 71 evaluates the fingerprint information acquired by the fingerprint acquisition unit 20, and the vein evaluation unit 72 evaluates the vein information acquired by the vein acquisition unit 30 (step S22). Next, the angle comprehensive evaluation unit 73 performs a comprehensive evaluation of the angle θ based on the evaluation results of the fingerprint evaluation unit 71 and the vein evaluation unit 72 (step S23). Next, the angle comprehensive evaluation unit 73 outputs the result of comprehensive evaluation (step S24). The display device 106 displays the comprehensive evaluation result by the angle comprehensive evaluation unit 73 (step S25). Thereafter, the execution of the flowchart ends.

(Evaluation of fingerprint information)
Details of the fingerprint information evaluation by the fingerprint evaluation unit 71 will be described below. FIG. 12A is a diagram illustrating an example of a fingerprint image acquired by the fingerprint sensor 104. First, the evaluation using the monochrome ratio of the fingerprint area obtained from the fingerprint image will be described. The black-and-white ratio of the fingerprint area is an amount representing the ratio of the crest and trough of the fingerprint. Referring to FIG. 12B, when the force with which the finger is pressed on the reading surface of the fingerprint sensor 104 is weak, the white ratio in the fingerprint region increases. On the other hand, referring to FIG. 12C, if the force with which the finger is pressed against the reading surface of the fingerprint sensor 104 is strong, the ratio of black in the fingerprint region increases. Therefore, it is possible to determine the degree of finger pressing by detecting the black and white ratio of the fingerprint region. Specifically, if the black-and-white ratio of the fingerprint area is within a predetermined range, it can be determined that the angle θ is appropriate.

  Next, evaluation using the fingerprint center will be described. When the angle θ is large, only the fingertip hits the reading surface. In that case, the palm side of the fingerprint area obtained from the fingerprint image is missing. Therefore, it is possible to evaluate whether the angle θ is appropriate according to the position of the fingerprint center (the center of the fingerprint pattern) in the obtained fingerprint region. For example, in the obtained fingerprint region, when the shift amount by which the fingerprint center shifts to the palm side is larger than a predetermined value, it can be determined that the angle θ is not appropriate. The fingerprint center can be detected by using the technical content of Japanese Patent No. 2790689. Note that it is possible to evaluate whether or not the angle θ is appropriate according to the position of the specific point of the fingerprint in the fingerprint region, not limited to the fingerprint center.

  In addition, referring to FIG. 12A, if the finger is pressed too hard on the reading surface of the fingerprint sensor 104, not only the fingertip but also the region α in the root direction of the finger comes into contact with the reading surface of the fingerprint sensor 104. Become. Therefore, it is possible to evaluate whether or not the angle θ is appropriate by measuring the area of the region α. For example, it may be evaluated whether the angle θ is appropriate using the finger area detected on the palm side of the first joint.

  A procedure for detecting the black and white ratio of the fingerprint region, the center of the fingerprint, and the area on the palm side from the first joint will be described. First, the fingerprint image is segmented. Here, the segment refers to a group of areas, for example, “area of fingertip of index finger” and the like corresponds to one segment. A fingerprint center detection process is performed for each detected segment. It can be determined that the segment in which the fingerprint center is detected is the fingertip. Alternatively, the determination may be made simply based on the center coordinates of the segment. For example, in the example of FIG. 12A, the segment with the largest Y coordinate at the center of the segment can be determined as the fingertip segment.

Fingerprint image determination processing is performed using the fingertip region extracted by the above method. First, the number of white pixels Cw and black pixels Cb included in the fingertip region is counted, and the following ratio is calculated.

  As an example, when “R” is about 0.5, it can be determined that the angle θ is appropriate. On the other hand, when “R” is large (black ratio is high) or “R” is small (white ratio is high), it can be determined that the angle θ is inappropriate. Further, the detected fingerprint center coordinates are compared with the fingertip region, and when the fingerprint center is shifted in the palm direction of the fingertip region, it can be determined that only the tip of the finger is reflected. In this case, it can be determined that the angle θ is inappropriate. Further, when a segment is detected at a position where the Y coordinate value is smaller than the fingertip region, the area of the segment is detected. If the detected area is equal to or greater than a predetermined value, it can be determined that an area other than the fingertip is reflected more than necessary in the fingerprint image, and the angle θ can be determined to be inappropriate.

(Evaluation of vein information)
Next, details of the vein information evaluation performed by the vein evaluation unit 72 will be described. For example, the sharpness of the vein image can be used for evaluating the vein information. The “contrast” of the image can be used to determine the sharpness of the vein image. Since near infrared rays are absorbed by blood, veins appear black in vein images. Therefore, when the force is excessively applied to the hand and the blood flow in the vein is lowered, the contrast of the image is lowered. From the above, the sharpness of the vein image can be evaluated by evaluating the contrast of the vein image.

  There are various values for the definition representing the contrast of an image. In general, a value called “contrast ratio” used for evaluation of a display or the like is defined as contrast ratio = Lmax / Lmin, where Lmax is a luminance when displaying white and Lmin is a luminance when displaying black. be able to. However, when targeting a living body, it is difficult to expect stable values as Lmax and Lmin. Further, since the contrast ratio is a simple comparison of luminance values of images, it is not always appropriate as an evaluation index for authentication images.

Therefore, in this embodiment, the “contrast value C” shown below is used as an index of sharpness. First, the vein evaluation unit 72 executes a vein feature extraction process from a vein image. Various methods can be taken as specific methods of the feature extraction processing. For example, the reduced shape of the luminance value due to veins is represented by a filter g (x, y), and the convolution operation between the filter g (x, y) and the input image f (x, y) is expressed by the following equation (2). (Expressed with *)

A region where the value of h (x, y) in the above formula (2) exceeds a predetermined threshold is represented as a feature region X, and the other region is represented as a region Y. Here, the vein contrast value C is defined as in the following formula (3).

  Note that <> X and <> Y represent average values in the region X and the region Y, respectively. When the vein is displayed darkly, the value of <f (x, y)> X becomes small (the luminance value decreases), and the contrast value C becomes a large value. On the other hand, when the blood flow decreases and the veins become thin, the contrast value C becomes a small value. From the above, by measuring the contrast value C, the sharpness of the vein image can be measured. Note that the sharpness index is not limited to the contrast value C, but in the following example, the sharpness will be described using the contrast value C.

  The vein image is taken using illumination, but the way the illumination hits is not always uniform. For this reason, the luminance value in the peripheral portion is lowered. In general, when photographing using a lens, the amount of light in the peripheral portion decreases (peripheral dimming). In such a case, in order to correctly measure the contrast value C, the brightness value may be corrected using a correction parameter measured in advance.

  The ratio between the luminance value of the palm and the luminance value of the vein is not constant. For example, there may be a user who originally has a thick and thick vein and a user who has a thin and thin vein. Therefore, it cannot be determined correctly by simple threshold processing. Therefore, referring to FIG. 13, a vein image may be determined by measuring a temporal change in contrast value C.

  The vein evaluation unit 72 stands by until the palm of the hand is stationary by calculating the contrast value C of the vein image continuously acquired by the vein sensor 105. The stillness of the palm can be determined using two images that are continuous with the distance to the palm. Specifically, when the distance is within a predetermined range and the difference between two consecutive vein images is equal to or less than a predetermined threshold value, it can be determined that the image is stationary.

The contrast value C at the time of detection of the stationary palm and C _1, the peak value of the still detection previous contrast value C and C _0. Here, the peak value C ₀ is photographed in a state where the palm is the most powerful immediately before the palm touches the guide of the vein sensor 105. Therefore, the image at this point is affected by blurring or a slight inclination. As a result, the vein image when the peak value _C0 is obtained is not suitable for authentication, but the contrast value C of the image at the time when the peak value _C0 is obtained becomes the maximum. According to the following equation (4), the amount of decrease ΔC from the peak value C _{0 of} C ₁ can be calculated, and ΔC can be used as a determination index for vein images.

(Comprehensive evaluation of angle θ)
The angle comprehensive evaluation unit 73 performs a comprehensive evaluation of the angle θ based on the evaluation of the fingerprint evaluation unit 71 and the vein evaluation unit 72. FIG. 14 is a diagram for explaining the comprehensive evaluation of the angle θ. Referring to FIG. 14, for example, when it is determined that the angle θ is large in the fingerprint information evaluation, the angle comprehensive evaluation unit 73 says that “the angle θ is large” as the comprehensive evaluation regardless of the vein information evaluation result. Output the result. In addition, when it is determined that the angle θ is small in the fingerprint information evaluation, the angle comprehensive evaluation unit 73 outputs a result that “the angle θ is small” as a comprehensive evaluation regardless of the evaluation result of the vein information.

  In addition, when the angle θ is determined to be appropriate (good) in the fingerprint information evaluation and the vein information is evaluated as “the angle θ is small” in the evaluation of the fingerprint information, the angle comprehensive evaluation unit 73 The result that “θ is small” is output. This is because the fingerprint is properly photographed, but it is considered that the blood flow is inhibited due to excessive force applied to the hand. Further, when the angle comprehensive evaluation unit 73 evaluates “appropriate” in both the fingerprint information and the vein information evaluation, it outputs a result that “the angle θ is appropriate”.

(Another example of angle θ evaluation)
In the comprehensive evaluation of the angle θ, it is determined whether or not the angle θ is appropriate. However, the angle θ may be quantitatively evaluated. In order to quantitatively evaluate the angle θ, the following value obtained by normalizing the evaluation amount used for evaluating the validity of the angle θ is used.

The value of the following formula (5) is a normalized value of ΔC, which is a value obtained by normalizing the amount of decrease in the vein contrast value C. When the value of the following formula (5) is larger than a predetermined value, it can be determined that the contrast is lowered.

The value of the following formula (6) is a normalized value of the black and white ratio of the fingerprint area. When the value of the following formula (6) is positive (when the ratio of black is high), it can be determined that the angle θ is large. On the other hand, when the value of the following formula (6) is negative (when the white ratio is high), it can be determined that the angle θ is small.

The value of the following formula (7) is a value obtained by normalizing the shift amount of the fingerprint center from the center of the obtained fingerprint region. Specifically, the distance D between the fingerprint center and the center of the fingertip region is normalized by a radius r when the fingertip region is approximated by a circle. That is, when the area of the fingertip region is S, the radius r when S is circularly approximated can be expressed as the following equation (8). When the distance D is normalized by this radius r, the following formula (7) is obtained. When the value of the following formula (7) is larger than the predetermined value, it can be determined that the fingerprint center is shifted.

The value of the following formula (9) is a value obtained by normalizing the area of the finger region other than the fingertip with the area of the fingertip region. “A” is the area of the region other than the fingertip, and “S” is the area of the fingertip region. When the value of the following formula (9) is larger than the predetermined value, it can be determined that the area of the finger region other than the fingertip is large.

The validity of the angle θ can be evaluated using the values of the above equations (5), (6), (7), and (9). FIG. 15 is an example of a flowchart for evaluating the validity of the angle θ. First, the angle comprehensive evaluation unit 73 determines whether or not any of the following formulas (10), (11), and (12) is satisfied (step S31). Th ₀ , Th ₁ , Th ₂ are threshold values.

When it determines with "No" in step S31, the angle comprehensive evaluation part 73 determines whether following formula (13) is materialized (step S32). Th ₃ is a threshold value. When it determines with "No" in step S32, the angle comprehensive evaluation part 73 determines whether following formula (14) is materialized (step S33). Th ₄ is a threshold value. When it is determined “No” in step S33, the angle comprehensive evaluation unit 73 determines that the angle θ is appropriate. Thereafter, the execution of the flowchart ends.

  When it determines with "Yes" in step S31, the angle comprehensive evaluation part 73 determines that angle (theta) is large (step S34). When it determines with "Yes" in step S32, the angle comprehensive evaluation part 73 determines that angle (theta) is small (step S35). When it is determined as “Yes” in Step S33, the angle comprehensive evaluation unit 73 determines that the angle θ is small. After the execution of steps S34 to S36, the execution of the flowchart ends. According to the flowchart of FIG. 15, it is possible to quantitatively evaluate whether or not the angle θ is appropriate.

  According to the present embodiment, it is possible to determine whether the angle θ is appropriate based on the fingerprint information acquired by the fingerprint sensor 104 and the vein information acquired by the vein sensor 105. Accordingly, the angle θ can be adjusted to a value suitable for acquisition of fingerprint information and vein information.

  FIG. 16 is a diagram for explaining a configuration in which the angle θ is variable. Referring to FIG. 16, an angle adjusting member 110 for adjusting the tilt angle of fingerprint sensor 104 may be provided. The angle adjustment member 110 is a member for manually adjusting the tilt angle of the fingerprint sensor 104.

  The angle adjustment member 110 includes a fulcrum 112 that supports the slope 111 on which the fingerprint sensor 104 is installed, a guide member 113 that guides the slope 111, and a fixing member 114 that fixes the slope 111 to the guide member 113. The guide member 113 guides the slope 111 by sliding, for example. The fixing member 114 is a screw or the like for fixing the slope 111 to the guide member 113. By tilting the slope 111 to a desired angle and fixing the slope 111 to the guide member 113 by the fixing member 114, the inclination angle of the slope 111 is fixed. By disposing the fingerprint sensor 104 on the slope 111, the fingerprint sensor 104 can be tilted to a desired angle.

  According to the configuration of FIG. 16, the inclination angle of the fingerprint sensor 104 can be easily adjusted. Thereby, the inclination angle of the reading surface of the fingerprint sensor 104 with respect to the reading surface of the vein sensor 105 can be adjusted according to the use environment of the biological information acquisition apparatus 100. In addition, by using the fixing member 114 to make the angle θ larger than 0 °, both the fingerprint information acquisition accuracy and the vein information acquisition accuracy can be improved.

Subsequently, the angle adjustment amount of the angle θ will be described. When it is determined that the angle θ is large, the evaluation value E ₊ may be calculated according to the following formula (15). When it is determined that the angle θ is small, the evaluation value E ₋ may be calculated according to the following equation (16). Note that “a ₀ ”, “a ₁ ”, “a ₂ ”, “a ₃ ”, “a ₀ ′”, and “a ₃ ′” are parameters representing weights for the respective evaluation values, and in this embodiment, Is a positive value.

When the angle θ is large, the evaluation value E ₊ can be used as an index indicating how large the angle θ is. On the other hand, when the angle θ is small, the evaluation value E ₋ is an index indicating how small the angle θ is. Using these evaluation values E ₊ and E ₋ , the change amount of the angle θ can be automatically calculated. For example, a table for a desired change amount Δθ of the angle θ with respect to the evaluation values E ₊ and E ₋ may be set in advance, and Δθ may be determined according to this table. The change amount Δθ of the angle θ can be calculated according to the following formula (17) and the following formula (18).

  It should be noted that appropriate values may be set in advance in the table of the weight parameter and the change amount Δθ of the angle θ through experiments or the like. The calculated Δθ may be displayed on the display device 106 or the like, and the user or the operator may adjust the angle θ. Alternatively, the angle θ may be automatically adjusted by an actuator or the like using the calculated Δθ.

  In the third embodiment, an example in which the angle θ is automatically adjusted using an actuator or the like according to the evaluation result of the angle comprehensive evaluation unit 73 will be described. FIG. 17A is a block diagram of each function realized by executing the biological information acquisition program according to the third embodiment. Referring to FIG. 17 (a), by executing the biometric information acquisition program, overall control unit 10, fingerprint acquisition unit 20, vein acquisition unit 30, authentication control unit 40, fingerprint verification unit 50, vein verification unit 60, angle evaluation The unit 70 and the angle adjustment unit 80 are realized. The registration database is stored in the storage device 103.

  In the present embodiment, an angle adjusting member 115 for automatically adjusting the tilt angle of the fingerprint sensor 104 may be provided with reference to FIG. The angle adjustment member 110 has power such as an actuator and adjusts the inclination angle of the fingerprint sensor 104 in accordance with an instruction from the angle adjustment unit 80. When the angle adjustment member 115 makes the angle θ larger than 0 °, both the fingerprint information acquisition accuracy and the vein information acquisition accuracy can be improved.

(Angle adjustment processing)
FIG. 18 is a diagram for explaining an example of a flowchart executed in the angle adjustment process. The angle adjustment process is a process of automatically adjusting the angle θ according to the result of the angle evaluation process. First, in accordance with an instruction from the authentication control unit 40, the fingerprint acquisition unit 20 acquires the user's fingerprint information from the fingerprint sensor 104, and the vein acquisition unit 30 acquires the user's vein information from the vein sensor 105 (step S41). Next, the angle evaluation unit 70 determines whether the angle θ is appropriate based on the fingerprint information and vein information acquired in step S41 (step S42). The process of step S42 is the same process as steps S22 to S25 of FIG.

  If it is determined as “Yes” in step S42, the execution of the flowchart ends. When it is determined as “No” in Step S42, the angle adjusting unit 80 adjusts the angle θ (Step S43). Specifically, when the angle evaluation unit 70 determines that the angle θ is large, the angle adjustment unit 80 decreases the angle θ by a predetermined value. When the angle evaluation unit 70 determines that the angle θ is small, the angle adjustment unit 80 increases the angle θ by a predetermined value. As the angle adjustment amount when adjusting the angle θ, the values of the above equations (17) and (18) can be used.

  According to the present embodiment, the angle θ is automatically adjusted to an appropriate value. Thereby, it is possible to improve both the fingerprint acquisition accuracy and the palm vein acquisition accuracy while suppressing a decrease in convenience.

  Note that since the optimum angle θ differs for each user, the adjusted angle θ may be used for narrowing down users to be verified for 1: N authentication. Specifically, first, the optimum angle θ set at the time of user registration is stored in the registration database. During the authentication process, the authentication control unit 40 compares the optimally adjusted angle θ with the optimal angle θ of all users stored in the registration database, and selects a user registered at a close angle. 1: N authentication is performed.

Or you may perform the comprehensive determination with the similarity which is an authentication result, and angle (theta). Specifically, when the similarity to a certain user n is S (n), the angle at the time of registration of the user n is θ (n), and the adjusted angle is θ, the total score according to the following equation (19) May be calculated. The total score is obtained by subtracting the difference (absolute value) of the optimum angle from the similarity. Here, “w” is a parameter representing a weight. By using T (n), information about the angle θ can be additionally added to the similarity of authentication results. By adopting such a configuration, it is possible to reflect an additional feature (an angle of warping of the hand) that has not been used in the past in the authentication process, so that a more accurate authentication process can be performed. become.

  In each of the above embodiments, the biological information acquisition apparatus 100 is not connected to a network, but is not limited thereto. For example, referring to FIG. 19, biometric information acquisition apparatus 100 may be connected to server 200 via a network. The server 200 includes a CPU 201, a RAM 202, a storage device 203, a communication unit 204, and the like. In the present embodiment, the biometric information acquisition apparatus 100 is provided with a communication unit 116 for transmitting and receiving signals to and from the server 200 via the network and communication unit 204.

  In this embodiment, the biometric information acquisition apparatus 100 implements the fingerprint acquisition unit 20, the vein acquisition unit 30, and the angle evaluation unit 70 by executing the biometric information acquisition program. Overall control unit 10, authentication control unit 40, fingerprint collation unit 50, and vein collation unit 60 may be implemented in server 200. Therefore, the registration database may be stored in the storage device 203 of the server 200.

  In each of the above embodiments, each function realized by executing the biometric information acquisition program may be substituted by using a dedicated circuit or the like. Further, in each of the above embodiments, the vein sensor 105 acquires a palm vein, but may acquire a vein of another part of the hand. For example, the finger vein that is the target of fingerprint reading by the fingerprint sensor 104 may be acquired. For example, a finger vein on the palm side of the first joint may be acquired. Even in this case, both the fingerprint acquisition accuracy and the palm vein acquisition accuracy can be improved by making the inclination angle of the reading surface of the fingerprint sensor 104 with respect to the reading surface of the vein sensor 105 larger than 0 °. Further, it may be determined whether the angle θ is appropriate based on the fingerprint information acquired by the fingerprint sensor 104 and the vein information acquired by the vein sensor 105.

  Although the embodiments of the present invention have been described in detail above, the present invention is not limited to such specific embodiments, and various modifications and changes can be made within the scope of the gist of the present invention described in the claims. It can be changed.

DESCRIPTION OF SYMBOLS 10 Overall control part 20 Fingerprint acquisition part 30 Vein acquisition part 40 Authentication control part 50 Fingerprint collation part 60 Vein collation part 70 Angle evaluation part 71 Fingerprint evaluation part 72 Vein evaluation part 73 Angle comprehensive evaluation part 80 Angle adjustment part 100 Biological information acquisition apparatus 101 CPU
102 RAM
DESCRIPTION OF SYMBOLS 103 Memory | storage device 104 Fingerprint sensor 105 Vein sensor 106 Display apparatus 107-109 Guide 110 Angle adjustment member 111 Slope 112 Support point 113 Guide member 114 Fixing member 115 Angle adjustment member

Claims (14)

A fingerprint sensor that reads fingerprints from the user's hand,
A vein sensor for reading a vein from the user's hand;
And an angle evaluation unit that evaluates an inclination angle of the reading surface of the fingerprint sensor with respect to the reading surface of the vein sensor. A fixing means for fixing an inclination angle of the reading surface of the fingerprint sensor with respect to the reading surface of the vein sensor;
The biological information acquiring apparatus according to claim 1, wherein the angle fixed by the fixing unit is variable.   The biological information acquisition apparatus according to claim 2, further comprising an angle adjustment unit that adjusts an inclination angle of the reading surface of the fingerprint sensor with respect to the reading surface of the vein sensor according to an evaluation result of the angle evaluation unit.   The biological information acquisition apparatus according to claim 3, wherein the angle adjustment unit adjusts an inclination angle of the reading surface of the fingerprint sensor with respect to the reading surface of the vein sensor to be larger than 0 °.   The angle evaluation unit evaluates an inclination angle of a reading surface of the fingerprint sensor with respect to a reading surface of the vein sensor according to a fingerprint read by the fingerprint sensor. The biological information acquisition device according to item.   The angle evaluation unit evaluates an inclination angle of a reading surface of the fingerprint sensor with respect to a reading surface of the vein sensor according to a density ratio of a fingerprint image read by the fingerprint sensor. The biological information acquisition apparatus according to any one of the above.   The angle evaluation unit evaluates an inclination angle of a reading surface of the fingerprint sensor with respect to a reading surface of the vein sensor according to coordinates of a specific point of a fingerprint read by the fingerprint sensor. The biological information acquisition device according to any one of the above.   The angle evaluation unit evaluates an inclination angle of the reading surface of the fingerprint sensor with respect to the reading surface of the vein sensor according to an area of a finger on the palm side of the first joint read by the fingerprint sensor. The biological information acquisition device according to any one of claims 1 to 4.   The angle evaluation unit evaluates an inclination angle of a reading surface of the fingerprint sensor with respect to a reading surface of the vein sensor according to a temporal change in contrast of a vein image read by the vein sensor. The biological information acquisition apparatus according to any one of claims 8 to 9. A fingerprint sensor that reads fingerprints from the user's hand,
A vein sensor for reading veins from the user's hand,
The biological information acquisition apparatus according to claim 1, wherein an inclination angle of the reading surface of the fingerprint sensor with respect to a reading surface of the vein sensor is larger than 0 °.   The biometric information acquisition apparatus according to any one of claims 1 to 10, wherein the fingerprint sensor is an optical sensor.   The biological information acquiring apparatus according to claim 1, further comprising a concave portion for placing a specific finger.   An evaluation step for evaluating the inclination angle of the reading surface of the fingerprint sensor with respect to the reading surface of the vein sensor when reading the fingerprint from the user's hand using the fingerprint sensor and reading the vein from the user's hand using the vein sensor. A biometric information acquisition method comprising: On the computer,
An evaluation step for evaluating the inclination angle of the reading surface of the fingerprint sensor with respect to the reading surface of the vein sensor when reading the fingerprint from the user's hand using the fingerprint sensor and reading the vein from the user's hand using the vein sensor. The biometric information acquisition program characterized by performing this.

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