Biological image acquisition apparatus and biological image acquisition method

Abstract

To convert biological information acquired by an arbitrary acquisition method into biological information that can be biometrically authenticated.SOLUTION: A biometric image acquisition device includes an acquisition unit that acquires a first biometric image in which an authentication site of a person to be authenticated used for biometric authentication is imaged, a determination unit that determines a magnification for converting a pixel density of the first biometric image into the same pixel density as a pixel density of a second biometric image registered in advance and collated with the first biometric image, and a conversion unit that resizes and outputs the first biometric image on the basis of the determined magnification.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present disclosure relates to a biometric image acquisition device and a biometric image acquisition method. [Background technology]

[0002] Patent Document 1 discloses a biometric information input device that is connected to an authentication device that identifies and authenticates individuals using fingerprint images, and transmits and inputs the fingerprint image to the authentication device. The biometric information input device includes a fingerprint input unit that has the function of capturing a fingerprint image, a biometric information conversion unit that converts the fingerprint image captured by the fingerprint input unit into image data having a predetermined vertical and horizontal resolution, vertical and horizontal image size, and ridge / valley light and dark relationship, and an input / output control unit that inputs the image data converted by the biometric information conversion unit to the authentication device. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Laid-Open No. 2008-217807 Summary of the Invention [Problem to be solved by the invention]

[0004] In Patent Document 1, taking into consideration the possibility of changes in the specifications of fingerprint input devices, the resolution and size of the fingerprint image are changed, and the image is converted into image data having a brightness relationship between ridges and valleys, thereby making it possible to support multiple models of fingerprint input devices (fingerprint scanners). However, changing the resolution or size of the image data can cause the brightness relationship between ridges and valleys to become unclear.

[0005] The present disclosure has been devised in consideration of the above-described conventional circumstances, and aims to provide a biometric image acquisition device and a biometric image acquisition method that convert biometric information acquired by any acquisition method into biometric information that can be biometrically authenticated. [Means for solving the problem]

[0006] The present disclosure provides a biometric image acquisition device including: an acquisition unit that acquires a first biometric image of an authentication part of a person to be authenticated, which is used for biometric authentication; a determination unit that determines a magnification for converting the pixel density of the first biometric image to the same pixel density as that of a second biometric image that is registered in advance and is to be matched with the first biometric image; and a conversion unit that resizes and outputs the first biometric image based on the determined magnification.

[0007] The present disclosure also provides a biometric image acquisition method performed by at least one processor, which acquires a first biometric image capturing an authentication part of a person to be authenticated that is used for biometric authentication, determines a magnification factor for converting the pixel density of the first biometric image to the same pixel density as that of a second biometric image that is registered in advance and is to be matched with the first biometric image, and resizes and outputs the first biometric image based on the determined magnification factor. [Effects of the Invention]

[0008] According to the present disclosure, biometric information acquired by any acquisition method can be converted into biometric information that can be biometrically authenticated. [Brief explanation of the drawings]

[0009] [Figure 1] FIG. 1 is a diagram showing a first use case example of a fingerprint acquisition device according to a first embodiment; [Figure 2] FIG. 10 is a diagram showing a second use case example of the fingerprint acquisition device according to the first embodiment. [Figure 3] FIG. 1 shows an example of capturing a fingerprint and measuring the fingerprint imaging distance according to the first embodiment. [Figure 4] FIG. 10 is a diagram showing an example of a scale conversion table. [Figure 5] A diagram showing an example of setting a target pixel density [Figure 6] FIG. 1 is a diagram showing a first example of an operation procedure of the fingerprint acquisition device according to the first embodiment; [Figure 7] FIG. 10 is a diagram showing an example of resizing a captured image in a first operation procedure. [Figure 8]FIG. 10 is a diagram showing a second example of an operation procedure of the fingerprint acquisition device according to the first embodiment; [Figure 9] FIG. 10 is a diagram showing an example of information on feature points acquired in a second operation procedure. [Figure 10] FIG. 10 is a diagram showing an example of capturing a fingerprint in the second embodiment; [Figure 11] FIG. 10 is a diagram showing an example of measuring the fingerprint imaging distance in the second embodiment. [Figure 12] FIG. 10 is a diagram showing a third example of an operation procedure of the fingerprint acquisition device according to the second embodiment. [Figure 13] FIG. 10 is a diagram showing a fourth example of an operation procedure of the fingerprint acquisition device according to the second embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0010] Hereinafter, with reference to the drawings as appropriate, detailed descriptions of embodiments that specifically disclose the configuration and operation of a biometric image acquisition device and a biometric image acquisition method according to the present disclosure will be provided. However, unnecessary detailed descriptions may be omitted. For example, detailed descriptions of well-known matters or redundant descriptions of substantially identical configurations may be omitted. This is to avoid unnecessary redundancy in the following description and to facilitate understanding by those skilled in the art. Note that the accompanying drawings and the following description are provided to enable those skilled in the art to fully understand the present disclosure and are not intended to limit the subject matter recited in the claims.

[0011] (Embodiment 1) <First use case example> A first use case example of the fingerprint acquisition device P1 according to the first embodiment will be described with reference to Fig. 1. Fig. 1 is a diagram showing the first use case example of the fingerprint acquisition device P1 according to the first embodiment. Note that in the following embodiments, a conversion process of biometric information when fingerprint authentication is performed will be described as an example of biometric authentication, but the biometric information used for biometric authentication is not limited to fingerprints. The biometric authentication may be, for example, vein authentication or palm print authentication, or authentication using any two or more biometric data of fingerprints, veins, and palm prints.

[0012] The fingerprint acquisition device P1 in the first use case example is used for fingerprint authentication, and captures an image of a user's fingertip (fingerprint) in a non-contact state with a glass surface or the like, and measures the imaging distance between the captured fingertip (fingerprint) and the camera 13. The fingerprint acquisition device P1 converts (resizes) the pixel density (pixels per inch (hereinafter sometimes referred to as "ppi")) of the captured image to the pixel density of the captured image of the fingerprint used to register the user's fingerprint (hereinafter referred to as the "registered image"), and acquires the captured image to be used for fingerprint authentication (i.e., matching with the registered image).

[0013] The fingerprint acquisition device P1 is realized by, for example, a smartphone, a tablet terminal, or a dedicated terminal for acquiring a user's fingerprint. The fingerprint acquisition device P1 includes a communication unit 10, a processor 11, a memory 12, a camera 13, a monitor 14, and a sensor 16. Note that the monitor 14 and the operation unit 15 are not essential components and may be omitted. Furthermore, if the camera 13 can realize the function of the sensor 16, the sensor 16 may be omitted.

[0014] The communication unit 10 is connected to an external device or server that performs fingerprint authentication using an image captured by the fingerprint acquisition devices P1 and P1A (i.e., an image of a fingerprint captured in a non-contact state) so as to be capable of wireless or wired communication. Note that the wireless communication here refers to short-range wireless communication such as Bluetooth (registered trademark) or NFC (registered trademark), or communication via a wireless local area network (LAN) such as Wi-Fi (registered trademark).

[0015] The processor 11 is configured using, for example, a central processing unit (CPU), a field programmable gate array (FPGA), or a graphics processing unit (GPU), and performs various processes and controls in cooperation with the memory 12. Specifically, the processor 11 references the programs and data stored in the memory 12 and executes the programs to realize the function of acquiring an image of the user's fingertip (fingerprint) that has the same pixel density as a registered image.

[0016] The memory 12 includes, for example, a random access memory (hereinafter referred to as "RAM") as a work memory used when executing each process of the processor 11, and a read only memory (hereinafter referred to as "ROM") that stores programs and data that define the operation of the processor 11. The RAM temporarily stores data or information generated or acquired by the processor 11. The ROM stores programs that define the operation of the processor 11.

[0017] Camera 13 is configured to have at least a lens (not shown) and an image sensor (not shown). The image sensor is, for example, a solid-state imaging element such as a Charged-Coupled Device (CCD) or a Complementary Metal Oxide Semiconductor (CMOS), and converts an optical image formed on an imaging surface into an electrical signal. Camera 13 starts capturing images in response to a control instruction to start capturing images input by processor 11 or a user's capture operation. Camera 13 outputs the captured image to processor 11.

[0018] The camera 13 may be configured to be capable of measuring the distance between the image sensor of the camera 13 and the user's fingertip, which is the subject, such as a laser ranging camera, a stereo camera, a Time-of-Flight (hereinafter referred to as "ToF") camera, or an Auto Focus (hereinafter referred to as "AF") camera. In such cases, the sensor 16, which will be described later, may be omitted from the configuration of the fingerprint acquisition devices P1 and P1A.

[0019] The monitor 14 is configured using, for example, a Liquid Crystal Display (LCD) or an organic electroluminescence (EL) display. The monitor 14 outputs and displays the captured image captured by the camera 13 or various screens generated by the processor 11. The various screens referred to here include a setting screen MN (see FIG. 5) for setting the pixel density of the captured image after resizing, i.e., the target pixel density to which the captured image is resized, or a screen (not shown) that notifies the result of fingerprint authentication performed by an external device or external server.

[0020] The operation unit 15 may be provided integrally with or separately from the monitor 14, and may be an interface configured with a touch panel, a mouse, a keyboard, etc. The operation unit 15 generates an electrical signal based on an input operation and outputs it to the processor 11.

[0021] The sensor 16 is realized by, for example, an infrared, ultrasonic, or ToF sensor, and measures the distance between the sensor 16 and the user's fingertip (fingerprint). The sensor 16 outputs information about the measured distance to the processor 11.

[0022] <Second use case example> Next, a second use case example of the fingerprint acquisition device P1A according to the embodiment 1 will be described with reference to Fig. 2. Fig. 2 is a diagram showing a second use case example of the fingerprint acquisition device P1A according to the embodiment 1.

[0023] In the second use case described below, the same components as those in the first use case are assigned the same reference numerals and their description will be omitted. Also, for ease of explanation, an example is shown in which the camera 13A and the sensor 16A are directly connected to the processor 11, but data transmission and reception between the camera 13A and the processor 11 and the sensor 16A may be performed via the communication unit 10A.

[0024] In the second use case example, the fingerprint acquisition device P1A acquires a captured image of the user's fingertip in a non-contact state during fingerprint authentication, and acquires information for calculating the imaging distance between the fingertip (fingerprint) and the camera 13A when the captured image was captured (for example, the focus position of the cameras 13 and 13A when capturing the image, or the distance between the fingertip (fingerprint) and the sensor 16A, etc.). Based on the information for calculating the imaging distance, the fingerprint acquisition device P1A converts (resizes) the pixel density of the captured image to the pixel density of the registered image, and acquires the captured image to be used for matching with the registered fingerprint (i.e., fingerprint authentication).

[0025] The fingerprint acquisition device P1A is realized by, for example, a personal computer (hereinafter referred to as "PC"), a notebook PC, a smartphone, a tablet terminal, or a dedicated terminal for acquiring a user's fingerprint. The fingerprint acquisition device P1A includes a communication unit 10A, a processor 11, a memory 12, and a monitor 14. The fingerprint acquisition device P1A is also connected to an externally attached camera 13A and a sensor 16A so as to be able to communicate data with each other. The monitor 14 and the operation unit 15 are not essential components and may be omitted. If the camera 13A can achieve the function of the sensor 16A (i.e., the function of acquiring information for calculating the imaging distance), the sensor 16A may be omitted.

[0026] The communication unit 10A is connected to an external device or an external server that performs fingerprint authentication using an image captured by the fingerprint acquisition device P1A (i.e., an image of a fingerprint captured in a non-contact state) via wireless or wired communication. The communication unit 10A is also connected to a camera 13A and a sensor 16A externally attached to the fingerprint acquisition device P1A so as to be able to transmit and receive data to and from each of them.

[0027] The processor 11 is configured using, for example, a CPU, FPGA, or GPU, and performs various processes and controls in cooperation with the memory 12. Specifically, the processor 11 references the programs and data stored in the memory 12 and executes the programs to realize the function of acquiring an image of the user's fingerprint that has the same pixel density as the registered image.

[0028] Camera 13A starts capturing images in response to a control instruction to start capturing images input by processor 11 or a user's capture operation. Camera 13A outputs the captured image to processor 11. Note that camera 13A may be configured to be able to measure the capturing distance, similar to camera 13. In such a case, sensor 16A, which will be described later, may be omitted.

[0029] The sensor 16A is realized by, for example, an infrared, ultrasonic, or ToF sensor, and measures the distance between the sensor 16 and the user's fingertip (fingerprint). The sensor 16 outputs information about the measured distance to the processor 11.

[0030] Next, an example of scale conversion based on the imaging distance of a fingertip (fingerprint) will be described with reference to Fig. 3. Fig. 3 is a diagram showing an example of imaging a fingerprint and measuring the imaging distance of the fingerprint according to embodiment 1. Fig. 4 is a diagram showing an example of scale conversion. Note that the positions of cameras 13, 13A and sensors 16, 16A shown in Fig. 3 are merely examples and are not limiting. Also, the example of scale conversion shown in Fig. 4 is merely an example and is not limiting.

[0031] The cameras 13 and 13A capture an image of a user's fingertip held within the angle of view of the cameras 13 and 13A. The cameras 13 and 13A output the captured image to the processor 11.

[0032] The sensors 16 and 16A measure the distance between the user's fingertip held within the angle of view of the cameras 13 and 13A and the sensors 16 and 16A in synchronization with the imaging timing of the cameras 13 and 13A. The sensors 16 and 16A output information about the measured distance to the processor 11.

[0033] The processor 11 measures the imaging distance between the user's finger and the image sensor of the camera 13, 13A when the captured image was captured, based on information about the distance between the user's finger and the sensor 16, 16A measured by the sensor 16, 16A and the positional relationship between the camera 13, 13A and the sensor 16, 16A. The processor 11 calculates the pixel density of the captured image based on the measured imaging distance.

[0034] The processor 11 determines a scale for resizing the captured image captured by the camera 13, 13A based on the scale (magnification) corresponding to the calculated pixel density. The processor 11 resizes the captured image at the determined scale and acquires the captured image to be used for fingerprint authentication.

[0035] 3, when a user's fingertip (fingerprint) is imaged in a non-contact state, the position of the user's fingertip (fingerprint) relative to the cameras 13 and 13A can be imaged at various imaging distances D0, D1, and D2. Therefore, the fingerprint acquisition devices P1 and P1 determine a scale (magnification) for resizing the pixel density of the image captured by the cameras 13 and 13A to the same pixel density as the pixel density of the registered image, based on scale conversion data previously stored in the memory 12.

[0036] The scale conversion data here is data in which pixel density (ppi) values ​​correspond to imaging distance D values, for example, as in the function f(D)=ppi shown in Fig. 4. The scale conversion data may be table data in which pixel density (ppi) values ​​correspond to imaging distance D values.

[0037] For example, when the imaging distance at which the captured image is captured is D1, the fingerprint acquisition devices P1, P1A calculate the pixel density (=600 ppi) of the captured image captured at imaging distance D1 based on the correspondence between the pixel density (ppi) value indicated by the scale conversion data and the value of the imaging distance D. When the calculated pixel density of the captured image is 600 ppi and the pixel density of the registered image is 500 ppi, the fingerprint acquisition devices P1, P1A calculate a scale (=500 ppi / 600 ppi) for converting the pixel density of the captured image (=600 ppi) to the pixel density of the registered image (=500 ppi). The fingerprint acquisition devices P1, P1A resize (reduce) the pixel density of the captured image based on the calculated scale (=500 ppi / 600 ppi).

[0038] Furthermore, when the imaging distance at which the captured image was captured is D2, the fingerprint acquisition devices P1, P1A calculate the pixel density (=400 ppi) of the captured image captured at imaging distance D2 based on the scale conversion data. When the calculated pixel density of the captured image is 400 ppi and the pixel density of the registered image is 500 ppi, the fingerprint acquisition devices P1, P1A calculate a scale (=500 ppi / 400 ppi) for converting the pixel density of the captured image (=400 ppi) to the pixel density of the registered image (=500 ppi). The fingerprint acquisition devices P1, P1A resize (enlarge) the pixel density of the captured image based on the calculated scale (=500 ppi / 400 ppi).

[0039] Next, a setting screen MN for setting a target pixel density will be described with reference to Fig. 5. Fig. 5 is a diagram showing an example of the setting screen MN for setting a target pixel density. Note that the setting screen MN shown in Fig. 5 is an example, and is not limited to this.

[0040] The target pixel density is the pixel density of the captured image converted for fingerprint authentication, and is the pixel density of the registered image. In the example shown in Fig. 5, when the pixel density of the registered image used for fingerprint authentication is predetermined, the fingerprint acquisition devices P1, P1A accept a setting operation of the target pixel density by an administrator who manages the fingerprint acquisition devices P1, P1A or a user via a setting screen MN.

[0041] The setting screen MN includes an input field INP that can accept input of a pixel density (ppi) value after conversion as a target pixel density. The fingerprint acquisition devices P1 and P1A accept an input operation of the target pixel density into the input field INP by an administrator or a user, and set the pixel density entered into the input field INP as the target pixel density.

[0042] <First operation procedure example> Next, a first example of an operation procedure of the fingerprint acquisition devices P1, P1A will be described with reference to Fig. 6. Fig. 6 is a diagram showing a first example of an operation procedure of the fingerprint acquisition devices P1, P1A according to the first embodiment.

[0043] The processor 11 of the fingerprint acquisition device P1, P1A acquires the captured image captured by the camera 13, 13A (St11).

[0044] When acquiring the imaging distance using the sensor 16, 16A, the processor 11 acquires information on the distance between the user's fingertip (fingerprint) and the sensor 16, 16A measured by the sensor 16, 16A (St12A). The processor 11 calculates and acquires the imaging distance of the fingertip (fingerprint) based on the distance between the user's fingertip (fingerprint) and the sensor 16, 16A output from the sensor 16, 16A and the positional relationship between the sensor 16, 16A and the camera 13, 13A (St12A).

[0045] When acquiring information about the imaging distance using the cameras 13 and 13A, the processor 11 acquires information about the focus position when an image of the user's fingertip is captured from the cameras 13 and 13A (St12B). The focus position may be either the autofocus or manual focus of the cameras 13 and 13A when capturing an image. When the cameras 13 and 13A are implemented as stereo cameras (i.e., two cameras), the processor 11 acquires two captured images captured by the two cameras, respectively, and acquires the imaging distance of the fingertip (fingerprint) based on the two acquired captured images.

[0046] The processor 11 calculates the pixel density of the captured image based on the calculated imaging distance (St13).

[0047] When processor 11 receives a request to set a target pixel density based on an operation by an administrator or a user, it generates a setting screen MN for receiving the setting of the target pixel density and displays it on monitor 14 (St14). Processor 11 receives an input operation for the target pixel density and sets the pixel density input in input field INP as the target pixel density. Note that the processing of step St14 is not essential and may be omitted.

[0048] The processor 11 calculates a scale (magnification) for resizing the captured image to the pixel density of the registered image or the target pixel density based on the scale conversion data recorded in the memory 12, the calculated pixel density of the captured image, and the pixel density of the registered image or the target pixel density (St15).

[0049] The processor 11 resizes the captured image based on the calculated scale (magnification) (St16). The processor 11 acquires the resized captured image as the captured image to be used for fingerprint authentication.

[0050] As described above, the fingerprint acquisition devices P1 and P1A according to embodiment 1 can more effectively suppress changes in fingerprint authentication accuracy due to changes in the distance between fingerprint feature points caused by differences in pixel density (i.e., resolution) by matching the pixel density of a registered image captured in a contact state where the fingerprint is in contact with a glass surface or the like with the pixel density of a captured image used for fingerprint authentication captured in a non-contact state where the fingerprint is not in contact with a glass surface or the like.

[0051] Next, the resizing process of the captured image will be described with reference to Fig. 7. Fig. 7 is a diagram showing an example of resizing of the captured image in the first operation procedure.

[0052] The enrollment image IMG11 is an image used for fingerprint authentication and includes minutiae Pt11, Pt12, Pt13, and Pt14 of the user's fingerprint.

[0053] Captured image IMG21 is an image captured by cameras 13, 13A of fingerprint acquisition devices P1, P1A, and is an image before resizing. Captured image IMG21 includes feature points Pt21, Pt22, Pt23, and Pt24 of a user's fingerprint. Here, the distances between the feature points P21 to P24 included in captured image IMG21 are different from the distances between the feature points Pt11 to Pt14 included in registered image IMG11.

[0054] The fingerprint acquisition devices P1 and P1A perform a scale calculation process to match the pixel density of the captured image IMG21 to the pixel density of the registered image IMG11, and a resizing process of the captured image IMG21 based on the calculated scale, thereby generating a captured image IMG21A.

[0055] Captured image IMG21A is an image obtained by resizing captured image IMG21 by fingerprint acquisition devices P1 and P1A, and has the same pixel density as registered image IMG11. Captured image IMG21A includes feature points Pt21A, Pt22A, Pt23A, and Pt24A of the user's fingerprint. The distances between the feature points Pt21A to Pt24A included in captured image IMG21A are approximately the same as the distances between the feature points Pt11 to Pt14 included in registered image IMG11.

[0056] As a result, the fingerprint acquisition devices P1 and P1A can generate an image IMG21A, thereby enabling fingerprint authentication by matching multiple feature points contained in the registered image IMG11 with multiple feature points contained in the image IMG21A, thereby more effectively suppressing a decrease in the authentication accuracy of fingerprint authentication.

[0057] In the first operating procedure described above, an example has been shown in which the fingerprint acquisition devices P1 and P1A acquire an image to be used for fingerprint authentication by resizing the image to change the pixel density of the image to match the pixel density of the registered image.

[0058] Here, the quality of the captured image may be degraded depending on the scale (magnification) of the resizing process. If the quality is degraded, the ridges and valleys of the fingerprint in the captured image may become blurred compared to before resizing, and the number of obtainable feature points may decrease. Therefore, the following second example of operation procedures will be described in which the fingerprint acquisition devices P1 and P1A acquire multiple feature points included in the captured image, resize the captured image, and convert the positions of the multiple feature points in accordance with the resizing process.

[0059] In the second example of the operating procedure, the processor 11A of the fingerprint acquisition device P1, P1A further realizes the function of acquiring multiple feature points contained in the captured image, acquiring information on the captured image and the multiple feature points, and converting the positions of the multiple feature points based on the scale of the resized captured image.

[0060] <Second example of operation procedure> Next, a second example of the operation procedure of the fingerprint acquisition devices P1, P1A will be described with reference to Fig. 8. Fig. 8 is a diagram showing a second example of the operation procedure of the fingerprint acquisition devices P1, P1A according to the first embodiment.

[0061] The second operation procedure here is an operation procedure for acquiring a captured image of a fingerprint in a non-contact state by resizing not only the captured image but also the positions of multiple feature points included in the captured image. Note that the processing of steps St11 to St16 in the second operation procedure shown in Fig. 8 is the same as the processing of steps St11 to St16 in the first operation procedure shown in Fig. 6, and therefore description thereof will be omitted.

[0062] The processor 11A of the fingerprint acquisition device P1, P1A acquires information on a plurality of fingerprint feature points that indicate the individuality of the user and are included in the captured image before resizing (St17). The fingerprint acquisition device P1, P1A outputs the resized captured image in association with information on each feature point after resizing or before and after resizing.

[0063] After resizing the captured image, the processor 11A converts the positions of the multiple feature points of the fingerprint acquired from the captured image before resizing at the same scale (magnification) as the scale at which the captured image was resized (St18). In the example shown in Fig. 7, the processor 11A converts the positions of the multiple feature points using the intersection of the x-axis and the y-axis as the reference point. As a result, the positions of the multiple feature points of the captured image are adjusted to positions corresponding to the resized captured image.

[0064] As described above, the fingerprint acquisition devices P1 and P1A according to the first embodiment can retain information on the positional relationships between multiple feature points contained in the captured image before resizing, even if the image quality of the captured image deteriorates due to resizing.By associating the captured image with information on each feature point after resizing or before and after resizing, the fingerprint acquisition devices P1 and P1A can acquire information on feature points necessary for fingerprint authentication, even if sufficient feature points cannot be acquired from the captured image due to deterioration in image quality of the captured image.Note that the fingerprint acquisition devices P1 and P1A may output the captured image, information on the scale at which the captured image is resized, and information on each feature point before resizing, in association with each other.

[0065] Next, the information on feature points will be described with reference to Fig. 9. Fig. 9 is a diagram showing an example of the information on feature points acquired in the second operation procedure. Note that in the example shown in Fig. 9, the information on each feature point is shown in a table to make the explanation easier to understand, but the present invention is not limited to this.

[0066] The processor 11A of the fingerprint acquisition devices P1, P1A performs image analysis of the fingerprint pattern from the captured image IMG21 and acquires minutiae Pt21 to Pt24 of the image-analyzed fingerprint pattern. Specifically, the processor 11A acquires the positions of the minutiae (i.e., the positions (coordinates) of the end or branching points of the pattern), the type of pattern corresponding to the minutiae, the angle of the tangent direction of the pattern, etc., based on the fingerprint pattern acquired by the image analysis. Note that the minutiae information acquired by the processor 11A is not limited to the examples described above.

[0067] The coordinates before resizing are the positions (coordinates) of the minutiae extracted from the captured image IMG21 before resizing. If the pattern does not branch, the processor 11A acquires the end point Pt31 of the fingerprint pattern as the position (coordinates) of the minutiae. If the pattern branches, the processor 11A acquires the branch point Pt32 of the fingerprint pattern as the position (coordinates) of the minutiae.

[0068] The post-resizing coordinates are the positions (coordinates) of the feature points converted based on the scale (magnification) used during resizing, and are equal to the positions (coordinates) of the feature points included in the resized captured image IMG21A.

[0069] The type of pattern indicates whether the position of the minutia is at the end of the pattern or at the branching point of the pattern.

[0070] The pattern angle indicates the angle of the tangent direction of the pattern at the position (coordinates) of the feature point. For example, the pattern angle is the angle of the tangent line LN31A of the pattern LN31 at the feature point (end point Pt31) or the angle of the tangent line LN32A of the pattern LN32 at the feature point (branch point Pt32). The pattern angle is also defined as the angle in the rotation direction A (see FIG. 7) around an axis perpendicular to the x-axis and y-axis of the captured image IMG21 shown in FIG. 7. As an example, the x-axis is set to 0 (zero) degrees here.

[0071] In the example shown in FIG. 9, the pattern end portion Pt31 has a pattern type of "end" and the angle of the tangent line LN31A of the pattern at the end portion Pt31 is "120°." The position (coordinates) before resizing is (x11, y11), and the position (coordinates) after resizing is (x21, y21). The pattern branch portion Pt32 has a pattern type of "branch" and the angle of the tangent line LN32A of the pattern at the branch portion Pt32 is "45°." The position (coordinates) before resizing is (x12, y12), and the position (coordinates) after resizing is (x22, y22).

[0072] (Embodiment 2) The fingerprint acquisition devices P1 and P1A according to the first embodiment described above have shown an example in which a captured image is resized and the pixel density of the captured image is changed based on information about the imaging distance of a fingertip (fingerprint) acquired by an arbitrary method. The fingerprint acquisition devices P1 and P1A according to the second embodiment described below will acquire information about the imaging distance by capturing an image of a depth chart and a user's finger, and resize the captured image and change the pixel density of the captured image based on the acquired information about the imaging distance.

[0073] The fingerprint acquisition devices P1, P1A according to the second embodiment have the same configuration and functions as the fingerprint acquisition devices P1, P1A according to the first embodiment, but do not include the sensors 16, 16A. Therefore, in the following description of the second embodiment, the same configuration and functions as those of the fingerprint acquisition devices P1, P1A according to the first embodiment will not be described.

[0074] First, a captured image IMG3 captured in the second embodiment and functions of the fingerprint acquisition devices P1 and P1A will be described with reference to Fig. 10 and Fig. 11. Fig. 10 is a diagram showing an example of capturing a fingerprint in the second embodiment. Fig. 11 is a diagram showing an example of measuring the fingerprint imaging distance in the second embodiment. Note that the arrangement of the depth chart DC shown in Fig. 10 is an example and is not limited to this.

[0075] In the second embodiment, the cameras 13 and 13A focus on the user's fingertip (fingerprint) in a non-contact state and capture an image so that the depth chart falls within the angle of view of the cameras 13 and 13A. The processor 11B detects the depth chart DC and the user's fingerprint from the captured image IMG3.

[0076] Here, the depth chart DC will be described. As an example, the depth chart DC has the shape of a right-angled isosceles triangle when viewed from the side of the user's fingertip, as shown in Fig. 11. As shown in Fig. 10, the depth chart DC has a scale indicating depth at intervals of a distance of √2 on the surface on the side to be imaged (i.e., the surface corresponding to the ratio √2 of the three sides of the right-angled isosceles triangle having a ratio of 1:1:√2).

[0077] The processor 11B performs image processing (e.g., contrast detection, edge detection, or frequency detection) on the detected depth chart DC to detect the scale that is in best focus among the scales provided on the depth chart DC. Based on the detected scale, the processor 11B measures the distance between the image sensor of the camera 13, 13A and the user's fingertip, which is the subject. For example, in the example shown in FIG. 11, the processor 11B measures the imaging distance to be D2 based on the scale on the depth chart DC.

[0078] <Third operation procedure example> Next, a third example of the operation procedure of the fingerprint acquisition devices P1, P1A will be described with reference to Fig. 12. Fig. 12 is a diagram showing a third example of the operation procedure of the fingerprint acquisition devices P1, P1A according to the second embodiment.

[0079] The third operation procedure here is an operation procedure for measuring the imaging distance of a fingertip (fingerprint) using a depth chart DC.

[0080] The processor 11B of the fingerprint acquisition device P1, P1A acquires the captured image IMG3 captured by the camera 13, 13A (St21). The captured image IMG3 is captured by using the autofocus function or manual focus function of the camera 13, 13A to focus on at least one fingertip that is the target of fingerprint authentication.

[0081] The processor 11B performs image processing on the captured image IMG3 to detect the depth chart DC. The processor 11B detects the scale that is in best focus among the detected scales, and measures the imaging distance of the fingertip (fingerprint) captured in the captured image IMG3 based on the detected scale (St22).

[0082] The processor 11B calculates the pixel density of the captured image IMG3 based on the measured imaging distance (St23).

[0083] When processor 11B receives a request to set a target pixel density based on an operation by an administrator or a user, it generates a setting screen MN for receiving the setting of the target pixel density and displays it on monitor 14 (St24). Processor 11B receives an input operation for the target pixel density and sets the pixel density input in input field INP as the target pixel density. Note that the processing of step St24 is not essential and may be omitted.

[0084] Processor 11B calculates a scale (magnification) for resizing the captured image to the pixel density of the registered image or the target pixel density based on the scale conversion data recorded in memory 12, the calculated pixel density, and the pixel density of the registered image or the target pixel density (St25).

[0085] The processor 11B resizes the captured image based on the calculated scale (magnification) (St26). The processor 11B acquires the resized captured image as the captured image to be used for fingerprint authentication.

[0086] As described above, the fingerprint acquisition devices P1 and P1A according to the second embodiment can match the pixel density of a captured image used for fingerprint authentication, captured in a non-contact state where the fingerprint is not in contact with a glass surface, etc., to the pixel density of a registered image captured in a contact state where the fingerprint is in contact with a glass surface, etc., based on the imaging distance measured using the depth chart DC. Therefore, the fingerprint acquisition devices P1 and P1A can more effectively suppress changes in fingerprint authentication accuracy due to changes in the distance between fingerprint minutiae caused by differences in pixel density (i.e., resolution).

[0087] (Embodiment 3) The fingerprint acquisition devices P1 and P1A according to the above-mentioned embodiments 1 and 2 have been described as examples in which the registered image is a captured image captured with the user's fingertip in contact with the fingerprint acquisition device. The fingerprint acquisition devices P1 and P1A according to the following embodiment 3 will be described as examples in which the registered image is a captured image captured with the user's fingertip in a non-contact state.

[0088] The fingerprint acquisition devices P1 and P1A according to embodiment 3 have the same configuration and functions as the fingerprint acquisition devices P1 and P1A according to embodiment 1. Therefore, in the following description of embodiment 3, the description of the same configuration and functions as the fingerprint acquisition devices P1 and P1A according to embodiment 1 will be omitted.

[0089] <Fourth example of operation procedure> A fourth example of the operation procedure of the fingerprint acquisition devices P1, P1A will be described with reference to Fig. 13. Fig. 13 is a diagram showing a fourth example of the operation procedure of the fingerprint acquisition devices P1, P1A according to the third embodiment.

[0090] The fourth operation procedure here will be described as an example of resizing an image of a user's fingerprint used for fingerprint authentication and changing the pixel density of the captured image based on the pixel density of a registered image captured when the user's fingertip is not in contact.

[0091] The processor 11C of the fingerprint acquisition device P1, P1A acquires a registration image to be used for fingerprint authentication (St31). If the registration image is stored (registered) in an external device or an external server, the processor 11C acquires the registration image from the external device or the external server.

[0092] The processor 11C acquires information about the imaging distance of the fingertip (fingerprint) when the registration image was captured, based on the metadata of the acquired registration image or the scale of the depth chart DC shown in the registration image (St32).

[0093] The processor 11C calculates the pixel density of the registered image based on information about the imaging distance of the fingertip (fingerprint) captured in the registered image (St33).

[0094] The processor 11C acquires a captured image captured by the camera 13, 13A (St34). The processor 11C calculates information on the imaging distance of the fingertip (fingerprint) shown in the acquired captured image (St35). Note that the acquisition of the imaging distance of the fingertip (fingerprint) shown in the captured image may be performed using the sensor 16, 16A, or may be performed using the focus position of the camera 13, 13A.

[0095] The processor 11C calculates the pixel density of the captured image based on the calculated imaging distance (St36).

[0096] Here, if the pixel density of the registered image is known, the processor 11C may accept a request to set the target pixel density based on an operation by an administrator or a user. The processor 11C accepts an input operation of the target pixel density on the setting screen MN that accepts the setting of the target pixel density, and sets the pixel density input in the input field INP as the target pixel density (St37).

[0097] The processor 11C calculates the scale (magnification) for resizing the captured image to the pixel density of the registered image or the target pixel density based on the scale conversion data recorded in the memory 12, the calculated pixel density of the captured image, and the pixel density of the registered image or the target pixel density (St38).

[0098] The processor 11C resizes the captured image based on the calculated scale (magnification) (St39). The processor 11C acquires the resized captured image as the captured image to be used for fingerprint authentication.

[0099] As described above, in the fingerprint acquisition devices P1 and P1A according to embodiment 3, even if the registered image is an image of a fingerprint captured in a non-contact state, if the pixel density of the registered image can be obtained by calculation or is known, the pixel density of the captured image used for fingerprint authentication can be matched, thereby more effectively suppressing changes in fingerprint authentication accuracy due to changes in the distance between fingerprint feature points caused by differences in pixel density (i.e., resolution).

[0100] (Addendum) The above description of each embodiment discloses the following techniques.

[0101] (Technology 1) an acquisition unit (communication unit 10, 10A) that acquires a first biometric image (captured image IMG21) of an authentication part (e.g., a fingerprint) of a person to be authenticated (user) used for biometric authentication (e.g., fingerprint authentication); a determination unit (processor 11, 11A, 11B, 11C) that determines a magnification (scale) for converting the pixel density of the first biometric image (captured image IMG21) to the same pixel density as the pixel density of a second biometric image (registered image IMG11) that is registered in advance and is to be compared with the first biometric image (captured image IMG21); a conversion unit (processor 11, 11A, 11B, 11C) that resizes and outputs the first biological image (captured image IMG21) based on the determined magnification (scale), Biometric image capture device (fingerprint capture devices P1, P1A). This allows the fingerprint acquisition devices P1 and P1A to match the pixel density of the captured image used for authentication to the pixel density of the enrollment image, and the fingerprint acquisition devices P1 and P1A can more effectively suppress a decrease in authentication accuracy caused by a change in the distance between the multiple feature points of the user included in the enrollment image and the multiple feature points of the user included in the captured image due to a difference in pixel density (i.e., resolution).

[0102] (Technology 2) The apparatus further includes a calculation unit (processor 11, 11A, 11B, 11C) that calculates an imaging distance at which the first living body image (captured image IMG21) was captured, The determination unit (processor 11, 11A, 11B, 11C) determines the magnification (scale) based on the calculated imaging distance. A biometric image acquisition device (fingerprint acquisition device P1, P1A) according to (Technology 1). This allows the fingerprint acquisition devices P1 and P1A to match the pixel density of the captured image used for authentication to the pixel density of the registered image based on the imaging distance.

[0103] (Technology 3) The determination unit (processor 11, 11A, 11B, 11C) determines the magnification (scale) based on data in which the pixel density corresponds to the imaging distance. (Technology 2) The biometric image acquisition device (fingerprint acquisition device P1, P1A). This allows the fingerprint acquisition devices P1 and P1A to match the pixel density of the captured image used for authentication to the pixel density of the registered image based on the imaging distance of the captured image used for authentication.

[0104] (Technology 4) The acquisition unit (communication unit 10, 10A) acquires the first biometric image (captured image IMG21) and a focus value of a camera that captured the first biometric image (captured image IMG21). The calculation unit (processor 11, 11A, 11B, 11C) calculates the imaging distance based on the focus value. (Technology 2) The biometric image acquisition device (fingerprint acquisition device P1, P1A). This allows the fingerprint acquisition devices P1 and P1A to calculate the imaging distance of the captured image based on the focus value of the cameras 13 and 13A.

[0105] (Technology 5) The acquisition unit (communication unit 10, 10A) acquires the first biometric image (captured image IMG21) and the position of the authentication region when the first biometric image (captured image IMG21) was captured from a sensor 16, 16A that detects the position of the authentication region. The calculation unit (processor 11, 11A, 11B, 11C) calculates the imaging distance based on the position of the authentication part. (Technology 2) The biometric image acquisition device (fingerprint acquisition device P1, P1A). This allows the fingerprint acquisition devices P1, P1A to calculate the imaging distance of the captured image based on the distance between the sensor 16, 16A and the fingertip (fingerprint) measured by the sensor 16, 16A.

[0106] (Technology 6) The first biometric image (captured image IMG21) is an image obtained by capturing the authentication portion and a depth chart DC indicating the position of the authentication portion, The calculation unit (processor 11, 11A, 11B, 11C) calculates the imaging distance based on the depth chart DC. (Technology 2) The biometric image acquisition device (fingerprint acquisition device P1, P1A). This allows the fingerprint acquisition devices P1 and P1A to calculate the imaging distance of the captured image based on the depth chart DC.

[0107] (Technology 7) a feature extraction unit (processor 11A) that extracts a plurality of feature points of the authentication portion from the first biometric image (captured image IMG21) and acquires the positions of the plurality of feature points; The conversion unit (processor 11A) resizes the first biometric image (captured image IMG21) based on the magnification (scale), converts positions of the plurality of feature points in the first biometric image (captured image IMG21) before resizing into positions corresponding to those in the first biometric image (captured image IMG21) after resizing, and outputs the converted positions. A biometric image acquisition device (fingerprint acquisition device P1, P1A) according to any one of (Technology 1) to (Technology 6). As a result, the fingerprint acquisition devices P1 and P1A can retain information on the positional relationships between multiple feature points contained in the captured image before resizing, even if the image quality of the captured image is deteriorated by resizing the captured image. Therefore, by associating the captured image with information on each feature point after resizing or before and after resizing, the fingerprint acquisition devices P1 and P1A can acquire information on feature points necessary for fingerprint authentication, even if sufficient feature points cannot be acquired from the captured image due to deterioration in image quality.

[0108] (Technology 8) The feature extraction unit (processor 11A) acquires the positions of the plurality of feature points and the type of feature of the authentication portion at the plurality of feature points (e.g., end point or branch). (Technology 7) The biometric image acquisition device (fingerprint acquisition device P1, P1A) described above. This allows the fingerprint acquisition devices P1 and P1A to hold information on the positional relationships between multiple feature points included in the captured image before resizing and the type of each feature point. Therefore, by associating the captured image with information on each feature point after resizing or before and after resizing, the fingerprint acquisition devices P1 and P1A can acquire information on feature points necessary for fingerprint authentication even when sufficient feature points cannot be acquired from the captured image due to deterioration in image quality of the captured image.

[0109] (Technology 9) The first biometric image (captured image IMG21) is an image of the authentication region captured in a non-contact state, The second biometric image (enrollment image IMG11) is an image of the authentication part captured in a contact state. A biometric image acquisition device (fingerprint acquisition devices P1, P1A) according to any one of (Technology 1) to (Technology 8). As a result, even if the imaging methods for the authentication area are different, the fingerprint acquisition devices P1 and P1A can more effectively suppress a decrease in authentication accuracy by resizing the pixel density of the captured image used for authentication to the same pixel density as the pixel density of the registered image.

[0110] (Technology 10) The first biometric image (captured image IMG21) and the second biometric image (registered image IMG11) are images of the authentication region captured in a non-contact state. A biometric image acquisition device (fingerprint acquisition devices P1, P1A) according to any one of (Technology 1) to (Technology 9). As a result, even if the method of imaging the authentication area is one in which the pixel density of the captured image is not determined, the fingerprint acquisition devices P1 and P1A can more effectively suppress a decrease in authentication accuracy by resizing the pixel density of the captured image used for authentication to the same pixel density as the pixel density of the registered image.

[0111] (Technology 11) A biometric image acquisition method performed by at least one processor 11, 11A, 11B, 11C, comprising: A first biometric image (captured image IMG21) is acquired by capturing an image of an authentication part (e.g., a fingerprint) of a person to be authenticated (user) used for biometric authentication (e.g., fingerprint authentication), and determining a magnification (scale) for converting the pixel density of the first biometric image (captured image IMG21) to the same pixel density as the pixel density of a second biometric image (registered image IMG11) that is registered in advance and is to be compared with the first biometric image (captured image IMG21); resizing the first biological image (captured image IMG21) based on the determined magnification (scale) and outputting the resized image; Biometric image acquisition method. This allows the processors 11, 11A, 11B, and 11C to match the pixel density of the captured image used for authentication to the pixel density of the registered image, and the processors 11, 11A, 11B, and 11C can more effectively suppress a decrease in authentication accuracy caused by a change in the distance between the multiple feature points of the user included in the registered image and the multiple feature points of the user included in the captured image due to a difference in pixel density (i.e., resolution).

[0112] Although various embodiments have been described above with reference to the accompanying drawings, the present disclosure is not limited to such examples. It is clear that those skilled in the art can conceive of various modifications, alterations, substitutions, additions, deletions, and equivalents within the scope of the claims, and it is understood that these also fall within the technical scope of the present disclosure. Furthermore, the components of the various embodiments described above may be combined in any manner without departing from the spirit of the invention. [Industrial Applicability]

[0113] The present disclosure is useful as a biometric image acquisition device and a biometric image acquisition method for converting biometric information acquired by any acquisition method into biometric information that can be biometrically authenticated. [Explanation of symbols]

[0114] 10,10A Communication section 11, 11A, 11B, 11C processors 12 Memory 13,13A Camera 14 monitors 15 Control section 16,16A sensor D,D0,D1,D2 Imaging distance DC Depth Chart IMG11 Registered image IMG21, IMG21A, IMG3 captured images MN setting screen P1,P1A Fingerprint acquisition device Pt11,Pt12,Pt13,Pt14,Pt21,Pt21A,Pt22,Pt22A,Pt23,Pt23A,Pt24,Pt24A Feature points Pt31 termination Pt32 branch

Claims

1. an acquisition unit that acquires a first biometric image of an authentication region of a person to be authenticated, the first biometric image being used for biometric authentication; a determination unit that determines a magnification factor for converting a pixel density of the first biometric image to a pixel density identical to a pixel density of a second biometric image that is registered in advance and is to be compared with the first biometric image; a conversion unit that resizes and outputs the first biometric image based on the determined magnification. Biometric image acquisition device.

2. a calculation unit that calculates an imaging distance at which the first biological image is captured, The determination unit determines the magnification (scale) based on the calculated imaging distance. The biometric image acquisition device according to claim 1 .

3. the determination unit determines the magnification based on data in which the pixel density corresponds to the imaging distance. The biometric image acquisition device according to claim 2 .

4. the acquisition unit acquires the first biometric image and a focus value of a camera used to capture the first biometric image; The calculation unit calculates the imaging distance based on the focus value. The biometric image acquisition device according to claim 2 .

5. the acquisition unit acquires the first biometric image and the position of the authentication part at the time the first biometric image was captured from a sensor that detects the position of the authentication part. the calculation unit calculates the imaging distance based on the position of the authentication part. The biometric image acquisition device according to claim 2 .

6. the first biometric image is an image obtained by capturing the authentication portion and a depth chart indicating the position of the authentication portion, The calculation unit calculates the imaging distance based on the depth chart. The biometric image acquisition device according to claim 2 .

7. a feature extraction unit that extracts a plurality of feature points of the authentication portion from the first biometric image and acquires positions of the plurality of feature points; the conversion unit resizes the first biometric image based on the magnification, converts positions of the plurality of feature points in the first biometric image before resizing into positions corresponding to those in the first biometric image after resizing, and outputs the converted image. The biometric image acquisition device according to claim 1 .

8. the feature extraction unit acquires positions of the plurality of feature points and types of features of the authentication portion at the plurality of feature points; The biometric image acquisition device according to claim 7 .

9. The first biometric image is an image of the authentication portion captured in a non-contact state, the second biometric image is an image of the authentication portion captured in a contact state; The biometric image acquisition device according to claim 1 .

10. the first biometric image and the second biometric image are images of the authentication portion captured in a non-contact state; The biometric image acquisition device according to claim 1 .

11. 1. A method for biometric image acquisition performed by at least one processor, comprising: acquiring a first biometric image of an authentication region of a person to be authenticated, the first biometric image being used for biometric authentication; determining a magnification factor for converting the pixel density of the first biometric image to the same pixel density as the pixel density of a second biometric image that is registered in advance and is to be matched with the first biometric image; resizing the first biometric image based on the determined magnification and outputting the resized image; Biometric image acquisition method.

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