JP2015127966A - Blood vessel image photographing device and personal authentication device - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide means for enabling personal authentication, such that psychological resistance is low, it is difficult to forge, and data on which individual features are reflected well can be acquired with good reproducibility, while eliminating or minimizing the need for a maintenance management operation for preventing a device from being stained.SOLUTION: A person authentication device which utilizes a vein pattern of a finger optimizes the quantity of light irradiation by a light source based upon a picked up finger image, and performs emphasis processing on the vein pattern in an image operation for authentication. Consequently, personal authentication such that psychological resistance is low, it is difficult to forge, and authentication precision is high can be performed while eliminating or minimizing the need for a maintenance management operation for preventing infection due to staining of the device and errors of acquired data.

Description

  The present invention relates to a technique for authenticating an individual using a vein pattern of a living body, particularly a finger.

  The current personal authentication technology is represented by fingerprint authentication. However, there is a problem that fingerprints of others are easy to obtain and can be counterfeited so that fingerprints can be collected at crime scenes in criminal investigations. For this reason, in recent years, personal authentication techniques other than fingerprint authentication have been developed. For example, Japanese Patent Application Laid-Open No. 7-21373 discloses a technique for performing personal authentication using a blood vessel pattern of a finger, and Japanese Patent Application Laid-Open No. 10-295673 discloses personal authentication using a vein pattern on the back of the hand. Technology is disclosed. These technologies irradiate the back of the finger or the hand, capture the reflected or transmitted light of the irradiated light, extract the blood vessel pattern from the captured image, and image the pre-registered blood vessel pattern. This is a technique of performing personal authentication by matching the blood vessel pattern.

JP 7-21373 A JP-A-10-295664

  There are several problems in realizing a personal authentication device using a finger vein pattern.

  One is the reproducibility of imaging. Conventional personal authentication devices are equipped with jigs for fixing the imaging location, such as pins and grip rods, but the fingers rotate or move in a plane or rotate around the finger length direction. The deviation of the imaging location due to such a situation occurs inevitably. Therefore, it is difficult to completely match the registered vein pattern and the vein pattern obtained at the time of authentication, and as a result, there is a problem that the authentication rate is lowered. In particular, in the case of a completely non-contact device, since it is impossible to perform imaging with a finger fixed to something, the deviation of the vein pattern at the time of registration and at the time of authentication is significant, and the reduction of the authentication rate becomes large. The other is the problem of the light source. None of the conventional personal authentication devices have a function of adjusting the amount of light emitted from the light source. Therefore, there is a problem that the image quality is low, such as the outline of the captured image is blurred, not sharp, or the contrast is weak, and correction processing is necessary to deal with it, so the image calculation becomes complicated, and consequently the authentication rate decreases Led to inviting.

  In this invention, said subject is solved by the following means.

  In the blood vessel image capturing device, the blood vessel imaging apparatus includes a plurality of light sources that irradiate light on the finger presented in the presentation area, and an imaging unit that can capture an image including a blood vessel of the finger. The number of light sources arranged in the short direction is smaller than the number of light sources arranged in the longitudinal direction.

  According to the present invention, it is possible to realize personal authentication that is highly reliable and safe and easy to use. In other words, it is possible to realize personal authentication with low psychological resistance, difficulty in counterfeiting, and high authentication accuracy while eliminating or minimizing maintenance work to prevent infection due to device contamination and errors in acquired data. The social significance of the present invention is extremely great.

The structural example of the apparatus which acquires the blood vessel image of the biological body by the optical method. FIG. Finger positioning method with low contact. Light source composed of arranged light emitting elements A three-dimensional imaging method using a three-dimensional arrangement of imaging elements. Procedures until the finger image is taken. Finger positioning method during authentication by air ejection. Authentication device using air jets. Device sterilization method in contact type authentication. Outline from finger image capture to authentication. Procedure from finger image capture to authentication. Registration image and authentication image creation processing method 1. Registration image and authentication image creation processing method 2 Method 1 for normalizing authentication calculation results. Normalization method 2 of the authentication calculation result.

  FIG. 1 is a basic configuration example of a personal authentication device. FIG. 2 shows an embodiment of the personal authentication device of the present invention. The apparatus includes a light source unit 101 for irradiating a finger with light, an imaging device 103 for imaging a finger, an arithmetic unit 104 for processing captured image data, and the like. As the light source, a semiconductor light source such as an LED (light emitting diode) is often used because it has good time response and is easy to control. A CCD camera was used as the imaging device. As the arithmetic unit 104, a personal computer is simply used, and an image is taken into the computer via an interface such as an image capture board. The computing device 104 performs an authentication computation on the acquired image. Reference numeral 201 denotes a window through which light from the light source passes. If the light source light leaks from the periphery of the finger, it is not preferable for image calculation. Therefore, an automatic opening / closing shutter for preventing this may be provided in the window. In addition to the window, an automatic opening / closing shutter can be provided between the light source and the finger. Reference numeral 202 denotes a pin for fixing the imaging position of the finger, but the pin may or may not be provided. In the absence of a pin, the device is completely non-contact. The vein pattern image formed by the transmitted light of the finger was captured by the imaging device 103.

  As the vein pattern for personal authentication, it is preferable to use the vein pattern on the palm side rather than the vein pattern on the back side of the finger. This is because the blood vessel pattern on the back side of the hand is always exposed to the outside of the body and there is a risk of being stolen. In this embodiment, all finger vein patterns are taken from the palm side vein pattern.

  FIG. 3A is a view of the light source unit 101 shown in FIG. 3B is a diagram of the positional relationship among the light emitting element 301, the positioning pin 205, the finger 302, and the imaging element 303 that constitute the light source, as viewed from the tip side of the finger. Reference numeral 304 denotes transmitted light.

  As shown in FIG. 4, a plurality of light-emitting elements constituting the light source are arranged and used in accordance with the shape of the finger. As the light source, a high-intensity light emitting LED in the near infrared wavelength region is often used, but a laser may be used. 401, 402, 405, 406 show front views of light sources of various shapes. Reference numeral 401 denotes a light source shape in which a plurality of mold type near-infrared light emitting diodes (near-infrared LEDs) conventionally used are arranged in a line. In the light source having the shape 401, since the outer edge of the light emitting portion is round, uneven brightness occurs when a plurality of light sources are arranged. Therefore, in 402, the outer edge portion of the mold type LED is cut off, and a plurality of the LEDs are arranged to form a light source. Reference numerals 407 and 408 are a front view and a cross-sectional view, respectively, of the LED with the outer edge portion cut off. A hatched portion 407 indicates a portion to be cut off. Reference numeral 403 denotes a cross-sectional view of 402, which is a light source in which a plurality of LEDs having the shapes shown in 407 and 408 are arranged. As a result, unevenness of light from the light source can be eliminated, the mounting density can be increased, and the light source intensity can be increased. Reference numeral 405 denotes an example in which a plurality of chip-type LEDs are arranged in a planar shape to serve as a light source. In any case, by arranging a plurality of LEDs, detecting the position of the placed finger based on the image monitored by the imaging device, and selecting the light source to be lit, the thickness and length of the finger can be determined. It is possible to form a corresponding light source.

  FIG. 6 shows a procedure up to imaging of a finger image. The light source always turns on weak light (601). It is detected whether or not the finger is held by the weak light (602). If there is a finger, the position of the finger is detected (603). The presence and position of the finger are detected based on the pixel value information of the monitor image. Based on the detected position information of the finger, the elements constituting the light source to emit light are determined (604). Furthermore, pixel value information of the image being monitored is acquired (605), and the amount of light emitted from the light source is optimized.

  The irradiation light quantity is optimized according to the following procedure. When the imaging target is a finger of a human limb, the joint portion has the highest light transmittance. Therefore, the joint portion is detected from the luminance profile in the long axis direction of the finger in the image data, and the peak value of the luminance is set as the luminance value (B) of the joint portion. This value is compared with the set luminance reference value (A). If A−B <0, feedback is applied to the light source to reduce the input current to the light source. If A−B> 0, the input current to the light source is increased. At the stage where A−B = 0, the adjustment of the light source quantity is terminated, and the image capture and calculation processing are executed. If this process is performed for each light emitting element, the area of the light emitting portion can also be optimized. In this case, as the light emitting element, a light emitting portion having a configuration like 405 in FIG. 4 in which chip-type small LEDs are arranged in a plane shape is suitable, and it corresponds to extreme differences in finger thickness and length. This is effective when performing illumination.

  The method shown above is a method for optimizing the light source light amount by adjusting the light source output, but the light source light amount may be optimized by adjusting the irradiation time of the light source.

  When optimizing the irradiation light amount, it is necessary to specify the joint portion. Two examples of procedures for that purpose will be described below. One is to detect a portion having a relatively high luminance value of the image based on the profile of the blood vessel pattern image of the finger imaged by transmitted light and identify the joint portion of the finger. Next, the light amount of the light source is fed back so that there is no pixel whose luminance value reaches 255 with respect to the intensity of the light source at the joint portion, for example, with respect to the dynamic range of 8 bits. Another procedure is to evaluate an image obtained by applying a spatial low-pass filter in the long axis direction of the finger in the acquired image, and adjust the light amount of the light source illuminating the joint portion. By the above procedure, a light source having a spatial intensity distribution can be configured.

  The configuration for automatically adjusting the irradiation light amount described above is suitable for acquiring a blood vessel image with good contrast. Since the image quality of the blood vessel image is dramatically improved by adjusting the amount of light, it is possible to smoothly perform personal authentication by the inter-image calculation of the acquired image.

  The calculation of authentication is performed by a correlation calculation that evaluates the similarity between the blood vessel pattern image of the finger captured at the time of authentication and the template using the blood vessel image of the person's finger registered in advance. The correlation calculation processing is performed by a calculation in which the calculation output value monotonically increases with respect to the degree of coincidence of elements constituting the two-dimensional array, most typically by a two-dimensional convolution calculation (Equation 1).

  One to five fingers can be registered, the number of fingers to be collated is increased according to the level of security, and blood vessel images other than fingers can be used in some cases. .

  FIG. 10 is a block diagram for explaining a procedure for performing personal authentication based on the detected finger image. The personal authentication process is roughly divided into two processes: a personal registration process and an authentication process. The personal registration process is a process of creating the registered image database 100 in advance based on the registration image input at the time of personal registration, and blocks 1000 to 1001 correspond to this. The authentication process is a process of determining approval or rejection based on a correlation calculation between an image input for authentication and a registered image, and blocks 1002 to 1005 correspond to this.

  In the personal registration process, the registration image of the personal person is input from the image detection means (block 1000), and at the same time, a registered image creation process (to be described later) is performed to create an image that emphasizes blood vessel running (block 1001) and register it. . On the other hand, in the authentication process, a personal ID is input by the personal information input means (block 1002), and at the same time, a corresponding registered image of the user is selected from the registered image database based on the personal ID (block 1003). Also, at the same time as the authentication image of the person to be authenticated is input from the image detection means (block 1004), an authentication image creation process, which will be described later, similar to the registered image creation process is performed to create an image that emphasizes blood vessel travel (block). 1005), the cross-correlation calculation is executed with the registered image.

  Subsequently, the correlation calculation result is evaluated, and an authentication result indicating whether or not the user is the user is output. As described above, the two-dimensional convolution calculation is most typically used as the correlation calculation. In this case, even if the finger moves in parallel in the image plane, the distribution obtained as a result of the two-dimensional convolution operation also moves in the same way, and the size and shape do not change. If the degree is evaluated, correction relating to parallel movement in the image plane is automatically performed. In addition, this correlation calculation utilizes the fact that the convolution calculation between two data is equivalent to the inverse Fourier transform of the product of the two Fourier transforms, and the two-dimensional fast Fourier transform (hereinafter referred to as “Fast Fourier Transform”). FFT).

  FIG. 11 is a block diagram illustrating an image calculation procedure when the correlation calculation is speeded up using FFT. The input registration image or authentication image is extracted by a contour extraction / rotation process (block 1101) so that the finger tilt is constant based on the contour contour. Perform rotation processing. With this process, even if the physical positioning of the finger is insufficient, the rotation in the image plane is corrected and positioned in the image space. Due to this and the feature of the two-dimensional correlation calculation, the movement in the image plane is corrected in both parallel movement and rotation and positioned in the image space.

  The registration image or authentication image that has undergone contour extraction / rotation processing is converted into an image that emphasizes blood vessel running (block 1102), and the result of two-dimensional FFT calculation processing (block 1103) is be registered. In the latter, an integration operation is performed with the registered image selected based on the ID input (block 1104). The result is subsequently subjected to a two-dimensional fast inverse Fourier transform (inverse FFT, hereinafter referred to as IFFT) (block 1105) to obtain a cross-correlation distribution between the registered image and the authentication image. As described above, in the registered image creation processing (block 1001) and the authentication image creation processing (block 1006), the same image processing corresponding to the processing from 1101 to 1103 is performed.

  FIG. 12 is a block diagram for explaining in detail an example of the blood vessel enhancement processing procedure. In FIG. 12, 12 (a) to 12 (c) are schematic views of finger images obtained for each processing procedure.

  The input image can be roughly divided into a finger part 120, an edge part 121, and a peripheral part 122. In general, various noises 123 are also included in the image, and it is necessary to remove them. In FIG. 12, blocks (1201) to (1203) are processing procedures for extracting the contour of the finger, and blocks (1204) to (1206) are images corresponding to the background (backtrend) other than the finger vein pattern. Processing steps, blocks (1207) to (1211) show processing steps for subtracting the back trend from the original image (1200) to extract only the necessary vein pattern.

  When the captured finger image is input (block 1200), first, a fine structure such as noise 123 is removed by the high frequency cutoff filter (block 1201), and only a relatively large structure such as a finger outline is emphasized. Subsequently, direction differentiation processing is performed (block 1202) to obtain an edge enhanced image 12 (b). As shown in the image 12 (b), since the edge portion 121 of the finger is emphasized and has a large pixel value in the edge-enhanced image, edge detection processing is performed based on the pixel value, and only the position information of the edge portion 121 is obtained. Is detected (block 1203). Subsequently, based on the detected edge position information, an image 12 (c) obtained by cutting out only the finger 120 from the original image 12 (a) is obtained (block 1204).

  In the image 12 (c), the average value of the pixel values outside the finger is matched with the average value of the pixel values inside the finger. If this calculation is not performed, the finger contour component emphasized by performing the finger greatly contributes to the calculation, and the authentication calculation based on the vein pattern is not performed.

  When the average value of the pixel values inside the finger is shifted to 0, the pixel value 0 is inserted into the peripheral portion 122 in the image 12 (c). Subsequently, after creating an image 12 (d) obtained by extrapolating the value of the peripheral portion 122 in the image 12 (c) in the vertical direction with the value of the edge portion 121 (block 1205), the image is roughly approximated by a high frequency cutoff filter. Only the structure, ie the back trend, is extracted (block 1206). Here, the reason why the extrapolation process is performed in the block 1205 is to prevent the pixel value in the vicinity of the edge portion 121 from being unintentionally emphasized by the high frequency cutoff filter process in the block 1206.

  Subsequently, after creating a difference image between the original image 12 (a) and the back trend image (block 1208), a cutout image 12 (e) of the difference image is obtained based on the detected edge position. The difference corresponds to a low-frequency cutoff filter process, which removes the back-trend structure generated by transmitted light and scattered light from muscles, bones, etc., so that only the blood vessel structure as shown in 12 (e) is emphasized. Images can be obtained.

  Finally, according to the finger inclination obtained from the detected edge position, an image 12 (f) that has been subjected to image rotation processing so that the inclination becomes a constant value, typically 0, is created (block 1209). This is output as a registered image or an authentication image (block 1210).

  FIG. 15 is a block diagram showing an authentication procedure after obtaining an authentication image by the procedure of FIG. The result of the cross-correlation calculation between the registered image and the authentication image is normalized by the following (Equation 2) (block 1503), and then the maximum value M in the distribution is extracted (block 1504).

  However, Cab (x, y) is a cross-correlation distribution between the registered image and the authentication image. The output of block 1209, Caa (x, y) and Cbb (x, y) mean the square integral value of the registered image and the registered image and the authentication image.

  If the calculated maximum cross-correlation value M between the registered image and the authentication image is greater than the threshold Mo, the person to be authenticated is considered to be the registrant and approval is performed (block 1009). On the other hand, if the value of M is smaller than the threshold value Mo, it is assumed that the person is not the person and the approval is rejected (block 1010). As the value of the threshold Mo, an appropriate value is obtained in advance by inputting a sample image and performing statistical processing. As described above, when the pixel average value inside the finger is shifted to 0, the value of Mo is about 0.45 to 0.55, but is not limited thereto.

  If the person is not confirmed, re-authentication is performed by re-inputting information such as finger image capturing within a predetermined number of preset times. For example, if it is confirmed that the person is an authorized person, access to the managed information or area is permitted. If the person is not confirmed, the user can re-apply within a specified number of times. If authentication is performed and it is not possible to confirm the identity of the person in the end, access to the managed information or area is denied.

  It is desirable that the personal information input means for inputting the person ID for selecting the person's registered image from the registered image database is performed by a non-contact method other than the keyboard. This can be done by inputting personal information such as names and passwords by voice or keywords that only the person knows, or using personal information mounted on a non-contact IC card or the like. By using such an input means, it is possible to construct a personal authentication system that makes use of non-contact features. This processing can be performed independently by the CPU in the authentication apparatus, or can be performed in conjunction with an online system through a device such as a computer.

  As the registered image for authentication, a fixed medium connected to the authentication server, a medium incorporating a semiconductor memory, or a portable medium represented by a flexible disk is used. With this method, the keyboard input operation in the current bank ATM can be omitted, and the problem of contactability and the troublesome maintenance of the apparatus can be eliminated. The use of this method is also suitable for access to personal information in electronic government and authentication in online commerce because of the above advantages.

  In the first embodiment, a finger is imaged using one CCD camera. However, a method of imaging a finger using a plurality of CCD cameras at the time of authentication or imaging is also effective as a method for increasing the authentication rate. It is.

  FIG. 5 shows an arrangement of the light source 301, the finger 302, and the CCD cameras (303-1 to 303-5) when a plurality of CCD cameras are used. A plurality of CCD cameras are used to capture a plurality of finger vein patterns from different directions, and a pattern closest to the registered vein pattern is selected for authentication. Alternatively, a plurality of registration vein patterns are imaged, the registration vein patterns are stored as three-dimensional data, and a pattern closest to the authentication vein pattern is selected for authentication. This method is particularly effective in preventing a decrease in the authentication rate when a finger rotates around the finger length direction as a central axis, and is effective in realizing a completely non-contact device.

  The captured image may be a moving image as well as a still image. When acquiring and registering three-dimensional data in a moving image, the moving image is picked up by rotating the finger in the configuration of the light source LED (301) and the finger (302) imaging element (303) in FIG. Alternatively, as shown in FIG. 5, imaging at a plurality of points may be performed using a plurality of CCD cameras. The authentication is performed using a two-dimensional image captured by the imaging unit configured as illustrated in FIG. 3 or an image captured three-dimensionally using the imaging unit configured as illustrated in FIG.

  The captured image is loaded into a computing device, and image computation is performed to perform authentication. However, the authentication vein ratio is selected by selecting the closest registration vein pattern and authentication vein pattern. There is an advantage that the load on image calculation is reduced.

  FIG. 13 is a block diagram for explaining in more detail one example of the blood vessel pattern enhancement processing (corresponding to blocks 1101 to 1103 in FIG. 11). When the finger image is input (block 1000 or 1004), the position of the contour of the finger is detected by edge detection processing (block 1300). Based on the edge position detected here, image rotation processing (block 1301) is performed so that the tilt of the finger becomes a constant value, typically 0. A blood vessel pattern enhancement process (block 1302) is performed on the obtained image.

  The blood vessel pattern enhancement processing is performed using, for example, a filter designed to cut off the high frequency with respect to the long axis direction of the finger and to cut off the low frequency with respect to the short axis direction of the finger as shown in FIG. . Filter processing can be performed in either the convolution calculation in the real space (Equation 1) or the integration calculation in the frequency space. For the blood vessel pattern enhancement processing image, based on the contour position of the finger detected by the previous edge detection processing (block 1300), as in the example of FIG. 12, the average value of the pixel values outside the finger is calculated as the pixel inside the finger. The average value is combined (block 1303). When the average value of the pixel values inside the finger is shifted to 0, the pixel values outside the contour are set to 0.

  After the two-dimensional FFT operation is performed on the obtained image (block 1103), an integration operation (block 1304) on the same image is performed, and a two-dimensional IFFT operation (block 1305) is performed. Evaluation function processing (block 1306) is performed on the result. The blood vessel of the finger mainly reflects that it travels in the long axis direction rather than the short axis direction of the finger, and the difference in blood vessel pattern is the peak shape in the short axis direction of the finger in the two-dimensional convolution calculation result. Especially well reflected. Therefore, as the evaluation function processing, for example, a kernel composed of elements only in the minor axis direction of the finger as represented by 13 (b) is used, and convolution calculation in real space or integration calculation in frequency space is performed. The process by is performed.

  If the input image is an m × n matrix and the kernel is a p × 1 matrix, the result of the evaluation function process is (m + p−1) × n columns. The maximum value Mx in the matrix of the result is calculated for the registered image and the authentication image, and is set as M1 and M2, respectively. M1 is stored in the registration database (100).

  FIG. 14 is a block diagram showing an authentication procedure after block 1007 when image processing is performed according to the procedure of FIG. An evaluation function process (block 1403) is performed on the result of the cross-correlation calculation between the registered image and the authentication image, and the maximum value M calculated there is expressed by the following (formula 3) based on the above M1 and M2. ) To perform a normalization operation (block 1404).

If the calculated cross-correlation index MX between the registered image and the authentication image is greater than the threshold value Mxo, the person to be authenticated is regarded as the registrant himself and approval is performed (block 1009). If the value of Mx is smaller than the threshold value Mxo, it is assumed that the user is not the registrant, and approval is rejected (block 1010). As the value of the threshold value Mxo, an appropriate value is obtained in advance by inputting a sample image and performing statistical processing. As described above, when the pixel average value inside the finger is shifted to 0, the value of Mxo is about 0.3 to 0.4, but is not limited thereto.

  In general, the completely non-contact method is not necessarily advantageous in terms of cost, processing time, downsizing, etc., so that the minimum necessary for finger positioning and the above non-contact features are maintained. An apparatus for fixing an imaging location such as a contact with a jig is also of great practical significance. Here, the bacteria present in human hands are overwhelmingly less on the back side of the hand than on the palm side. Therefore, it is desirable that the palm side of the device should not be brought into contact with the apparatus even if the imaging location is brought into contact with the fixing jig at the minimum. Here, an example will be described.

  FIG. 7 shows a finger positioning method using air ejection instead of the pins in FIG. The compressed air is ejected from the ejection port (FIG. 7 (700), FIG. 8 (800)). Reference numeral 802 denotes an air compressor and a control system, and reference numeral 801 denotes a compressed air inlet. In FIG. 8, the air ejected from the ejection port of the palm portion is for preventing the palm from touching the apparatus. At the time of authentication, the hand is naturally placed at a position where the air ejected from FIG. 7 (700) does not hit the finger strongly.

  Whether the height from the device to the palm position is appropriate is measured by installing an optical sensor to detect the position in the height direction, image capture is controlled, or the height is inappropriate Controls the means to inform the person to be authenticated. As described above, since the palm does not come into contact with the object, it is possible to reduce the risk of infection such as bacteria caused by an unspecified number of people using the device. This method, in which the palm side is not contacted, can be said to be an excellent method compared to the method in which the palm side is contacted.

  In addition, even if the device contacts the palm side, it is necessary to wind up from the surface using the sheet (900) on which the palm is placed or to sterilize with an ultraviolet light source (901) disinfectant (902) at the time of authentication. Thus, it is possible to realize an authentication device that takes advantage of the feature of the present invention that it can be used cleanly. In order to perform sufficient sterilization, a sheet coated with a photocatalyst such as titanium oxide is used as a sheet (900) on which a hand is placed, and is irradiated with ultraviolet rays. By incorporating such a sterilizer, the cleanliness of the device can be maintained.

300 ... hand, 903 ... authentication device case, 904 ... sterilization box, 905 ... ultraviolet light or disinfectant dispenser.

Claims (3)

A plurality of light sources arranged in a grid,
A presentation surface on which the hand is presented;
An imaging unit for imaging a plurality of fingers in the presented hand;
A blood vessel image photographing apparatus comprising: a light amount control unit that selects an irradiation light source corresponding to each of the plurality of fingers from the plurality of light sources, and controls a light amount of each of the irradiation light sources. .   The blood vessel image capturing apparatus according to claim 1, wherein the image captured by the image capturing unit is transmitted to an authentication unit that performs personal authentication. Multiple light sources;
A plurality of imaging units;
A light amount control unit for controlling the light amount of each of the plurality of light sources;
With
The blood vessel image capturing device, wherein the plurality of image capturing units capture an image including a presented blood vessel pattern of a finger.

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