Information processing method and program

Abstract

To provide a person authentication support system and a program for the person authentication support system that support improvement of accuracy of person authentication by confirming that information for identifying a target person is information of the target person concerned.SOLUTION: A program for a person authentication support system comprises steps of: acquiring information on depth measurement accuracy S301; acquiring depth information from a range according to the information on the depth measurement accuracy S303; and processing for a person authentication S307, including matching a person based on the depth information.SELECTED DRAWING: Figure 13

Description

[Technical field]

[0001] The present invention relates to an information processing method and a program. [Background technology]

[0002] For example, Patent Document 1 discloses an image processing device as a technology for authenticating an individual. The image processing device described in Patent Document 1 has an acquisition unit that acquires a first image generated by photographing a subject using light of a first wavelength, a second image generated by photographing the subject using light of a second wavelength, and depth information of the subject, and a detection unit that detects a face appearing in the second image.

[0003] The image processing device also has a determination unit that determines whether or not the face detected by the detection unit is a photograph of a living body based on depth information, and an extraction unit that extracts a facial image from the first image based on information about the face that the determination unit has determined to be a photograph of a living body. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] International Publication No. 2018 / 079031 Summary of the Invention [Problem to be solved by the invention]

[0005] According to the technology described in Patent Document 1, it is determined whether or not the face detected by the detection unit is a photograph of a living body based on the depth information. However, depending on a measurement device such as a sensor that generates the depth information, the accuracy of the generated depth information often varies. Therefore, it may be difficult to accurately determine whether or not the face in the image is a photograph of a living body, making accurate person authentication difficult.

[0006] The present invention has been made in consideration of the above-mentioned circumstances, and one of its objects is to help improve the accuracy of person authentication. [Means for solving the problem]

[0007] In order to achieve the above object, a program according to a first aspect of the present invention comprises: obtaining information regarding the accuracy of the depth measurement; obtaining depth information from a range corresponding to information on the depth measurement accuracy; A process of matching a person based on the depth information; to be executed by the computer.

[0008] In order to achieve the above object, an information processing method according to a second aspect of the present invention comprises: obtaining information regarding the accuracy of the depth measurement; obtaining depth information from a range corresponding to information on the depth measurement accuracy; A process of matching a person based on the depth information; The computer executes Effect of the Invention

[0009] According to the present invention, it is possible to support improvement in the accuracy of person authentication. [Brief description of the drawings]

[0010] [Figure 1] 1 is a diagram showing a configuration of a person authentication support system according to a first embodiment of the present invention. [Diagram 2] FIG. 4 is a diagram showing an example of a read image. [Diagram 3] FIG. 4 is a diagram showing an example of measurement condition-accuracy data according to the first embodiment. [Figure 4] FIG. 4 is a diagram showing a configuration of a region setting unit according to the first embodiment. [Diagram 5] FIG. 2 is a diagram illustrating a configuration of a collation / determination unit according to the first embodiment. [Figure 6]FIG. 2 is a diagram illustrating an example of a physical configuration of the measurement device according to the first embodiment of the present invention. [Figure 7] 1 is a diagram illustrating an example of a physical configuration of a person authentication support device according to a first embodiment of the present invention. [Figure 8] 5 is a flowchart showing an example of a measurement process according to the first embodiment of the present invention. [Figure 9] 11 is a diagram showing an example of an image of a shooting area SA displayed by a display unit. FIG. [Figure 10] 1 is a diagram showing an example of an image of a shooting area SA including a face of a subject. [Figure 11] 9 is a flowchart showing an example of the measurement information generating process shown in FIG. 8. [Figure 12] 13 is a diagram showing an example of a plurality of measurement points MP defined in association with an imaging area SA. FIG. [Figure 13] 5 is a flowchart showing an example of person authentication processing according to the first embodiment of the present invention. [Figure 14] 1 is a diagram showing an example of a face area FR identified from a shooting area SA. [Figure 15] 11 is a diagram showing an example of measurement points MP included in a face area FR. FIG. [Figure 16] FIG. 11 is a diagram showing a configuration of a person authentication support system according to a second embodiment of the present invention. [Figure 17] 11 is a flowchart showing an example of a measurement process according to the second embodiment of the present invention. [Figure 18] 18 is a flowchart showing an example of the measurement information generating process shown in FIG. 17. [Figure 19] 11 is a flowchart showing an example of person authentication processing according to the second embodiment of the present invention. [Figure 20] FIG. 13 is a diagram showing an example of measurement condition-accuracy data according to Modification 3. [Figure 21] FIG. 23 is a diagram showing a functional configuration of a person authentication support system according to Modification 8. [Figure 22] FIG. 23 is a diagram showing a functional configuration of a person authentication support device according to a ninth modified example. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0011] Hereinafter, embodiments of the present invention will be described with reference to the drawings. In all the drawings, the same components are given the same reference numerals, and the description will be omitted as appropriate.

[0012] <<Embodiment 1>> <Configuration of person authentication support system 100> The person authentication support system 100 according to the first embodiment of the present invention is a system that supports person authentication of a subject. In person authentication, information for identifying the subject is confirmed to be the subject's own. Such person authentication may be performed in a process that handles personal information of the subject, for example, when registering the subject as a member who will make a transaction in online shopping or the like. In this case, the information for identifying the subject is the name, address, date of birth, etc., input by the subject.

[0013] 1, the person authentication support system 100 includes a measurement device 101 and a person authentication support device 102. The measurement device 101 and the person authentication support device 102 are connected to each other via a network configured by a wired or wireless network or an appropriate combination of these networks so that they can transmit and receive information to and from each other.

[0014] Hereinafter, the person authentication support device 102 will also be referred to simply as the "support device 102."

[0015] <Functional configuration of the measuring device 101> The measuring device 101 is a device capable of generating information used to authenticate the subject, and functionally includes an input unit 103, a display unit 104, a reading unit 105, a depth measuring unit 106, a brightness measuring unit 107, and a communication unit 108.

[0016] The input unit 103 receives instructions from the subject. The display unit 104 displays information to the subject.

[0017] The reading unit 105 is composed of a camera 1070 (see FIG. 6) and the like, and captures an image of an imaging area SA including the face of a subject, and generates image information indicating the captured image of the imaging area SA.

[0018] Moreover, the reading unit 105 reads information shown on the personal identification document by photographing the personal identification document associated with the face image of the target person, and generates read image information showing the photographed read image M. The personal identification document is preferably an official document, such as a driver's license or a personal identification number card (so-called My Number card).

[0019] 2 shows an example of a read image M. The read image M shown in the figure includes a facial photograph of the subject on one side of the identification document, so that the facial image of the subject is associated with the identification document.

[0020] Referring again to FIG. The depth measurement unit 106 measures the depth of each of a plurality of measurement points MP that are predetermined in association with the shooting area SA shot by the reading unit 105, and generates depth information indicating the measured depth. The depth of each of the plurality of measurement points MP is the distance from the reading unit 105 to a point in real space that corresponds to each of the plurality of measurement points MP.

[0021] For example, when the reading unit 105 and the depth measuring unit 106 are respectively configured by a camera 1070 and a depth sensor 1090 (see FIG. 6), the camera 1070 and the depth sensor 1090 may be provided in positions close to each other in the measuring device 101. This makes it possible to practically measure the distance from the reading unit 105 to each of the measurement points MP.

[0022] The brightness measuring unit 107 is an illuminance sensor 1080 (see FIG. 6) that measures the brightness of the shooting environment when an image is shot by the reading unit 105, and generates brightness information indicating the measured brightness.

[0023] The communication unit 108 transmits and receives information to and from the support device 102 via the above-mentioned network. The communication unit 108 according to the present embodiment transmits image information, read image information, depth information, brightness information, and measurement condition information indicating the measurement conditions of depth to the support device 102 in response to an instruction from the subject.

[0024] The measurement condition information is information indicating the depth measurement conditions in the measuring device 101, and in this embodiment is OS (Operating System) information. The OS information is information for identifying the OS running in the measuring device 101, and indicates, for example, the type and version of the OS. The OS information is, for example, stored in advance in a storage unit (not shown) included in the measuring device 101, and is acquired by the communication unit 108.

[0025] <Functional configuration of the person authentication support device 102> The support device 102 judges whether or not to perform a matching process for authenticating the person of interest, based on the information generated by the measurement device 101. Then, the support device 102 performs a matching process or an authentication process for authenticating the person of interest, depending on the result of the judgment.

[0026] The support device 102 functionally includes a read image acquisition unit 110, an image information acquisition unit 111, a measurement condition acquisition unit 112, a brightness acquisition unit 113, a data memory unit 114, an area setting unit 115, a depth acquisition unit 116, a comparison judgment unit 117, and an authentication unit 118.

[0027] The read image acquisition unit 110 acquires read image information from the measurement device 101. The image information acquisition unit 111 acquires image information from the measurement device 101. The measurement condition acquisition unit 112 acquires measurement condition information from the measurement device 101. The brightness acquisition unit 113 acquires brightness information from the measurement device 101.

[0028] The data storage unit 114 is a storage unit in which measurement condition-accuracy data 114a is stored in advance. The measurement condition-accuracy data 114a is data in which measurement condition information and accuracy information are associated with each other, as shown in Fig. 3. The accuracy information is information that indicates the measurement accuracy of the depth.

[0029] In the measurement condition-accuracy data 114a illustrated in Fig. 3, the measurement condition information indicates the type of OS, and the accuracy information indicates the depth measurement accuracy. Specifically, in the measurement condition-accuracy data 113a illustrated in Fig. 3, the OS "A" is associated with a depth measurement accuracy of "150," and the OS "B" is associated with a depth measurement accuracy of "80."

[0030] The number of pieces of measurement condition information included in the measurement condition-accuracy data 114a is not limited to two, and may be changed as appropriate.

[0031] The area setting unit 115 sets a processing area according to the measurement conditions indicated by the measurement condition information acquired by the measurement condition acquisition unit 112. The processing area is an area of ​​the shooting area SA of the image acquired by the image information acquisition unit 111 that is to be subjected to depth information processing.

[0032] In detail, the region setting unit 115 functionally includes an accuracy determining unit 120 and a setting unit 121 as shown in FIG.

[0033] The accuracy determining unit 120 determines, based on the measurement condition information acquired by the measurement condition acquiring unit 112, whether or not the depth measurement accuracy is high.

[0034] The accuracy determination unit 120 in this embodiment determines whether the depth measurement accuracy is high or not depending on whether the measurement accuracy obtained based on the measurement condition information and the measurement condition-accuracy data 114a satisfies a predetermined measurement standard.

[0035] For example, the measurement criterion is that when the value indicated by the measurement accuracy information is equal to or greater than a predetermined threshold (e.g., "100"), the accuracy is high, and when the value indicated by the measurement accuracy information is less than the threshold, the accuracy is low.

[0036] When the measurement accuracy determined by the accuracy determining section 120 is high, the setting section 121 sets a narrower processing region than when the determined measurement accuracy is not high (that is, low).

[0037] For example, when the measurement accuracy is low, the processing area is the entire photographing area SA. When the measurement accuracy is high, the processing area is the face area FR. The face area FR is an area corresponding to the subject's face and is a part of the photographing area SA, and is therefore narrower than the entire photographing area SA.

[0038] Referring again to FIG. The depth acquisition unit 116 acquires depth information including the depth in the processing region set by the region setting unit 115 from the measurement device 101. The depth information acquired by the depth acquisition unit 116 indicates the depth measured under the measurement conditions indicated by the measurement information acquired by the measurement condition acquisition unit 112.

[0039] The depth acquisition unit 116 according to this embodiment acquires depth information from the measurement device 101 when the brightness measured by the brightness measurement unit 107 satisfies a predetermined illuminance standard.

[0040] The illuminance standard according to the present embodiment is, for example, specified as a range including the upper and lower limits of brightness. For example, if the upper limit is THU [candela] and the lower limit is THL [candela], the illuminance standard is that the brightness measured by the brightness measurement unit 107 is equal to or greater than THL [candela] and equal to or less than THU [candela].

[0041] Moreover, in this embodiment, the depth acquisition unit 116 acquires, from the measurement device 101, depth information indicating the depth of the entire imaging area SA.

[0042] The matching / determining section 117 determines, based on the depth information of the processing region set by the region setting section 115, whether or not to use the image information of the subject for matching processing.

[0043] The matching process is, for example, a process of matching an image indicated by the image information with the read image M, thereby confirming that the person included in the image indicated by the image information and the read image M is the same person (subject). In detail, for example, when the similarity of the feature amount of the face image of the person included in the image indicated by the image information and the read image M is equal to or greater than a predetermined threshold, it is presumed that the person included in the image indicated by the image information and the read image M is the same person. Also, when the similarity is less than the threshold, it is presumed that the person included in the image indicated by the image information and the read image M is not the same person.

[0044] Generally, a typical method of identity theft, in which a person is authenticated using another person's identification document, is to display an image of the person (the person) identified by the identification document on a display or monitor screen by a third party, who has previously photographed the person, and photograph the image displayed on the screen. According to this method, in a matching process based on the similarity of the features of the facial image of the subject contained in the image information and the read image M, it may be presumed that the person shown in the image information and the person contained in the read image M are the same person, even though the third party is attempting to authenticate the person using another person's identification document.

[0045] In order to prevent such spoofing, the matching and judging unit 117 checks the authenticity of the image information based on the depth information of the processing area set by the area setting unit 115. The authenticity of the image information means that the image of a person included in the image information was obtained by actually photographing a person (i.e., photographing a person who was actually present at the photographing location at the time of photographing when the image information was generated).

[0046] When an image displayed on a display or monitor screen is photographed, the screen is often flat, so the depth information indicates a generally flat surface, whereas when an image of an actual person is photographed, the depth information indicates unevenness to a certain degree. Therefore, the collation and judgment unit 117 can estimate the authenticity of the image information based on the depth information of the processing area.

[0047] Then, the matching judgment unit 117 judges that the image information of the subject should be used in the matching process if the image information is presumed to be authentic, and judges that the image information of the subject should not be used in the matching process if the image information is presumed to be authentic.

[0048] In detail, the collation and determination unit 117 includes an extraction unit 130 and a determination unit 131, as shown in FIG.

[0049] The extraction unit 130 extracts the depth information of the processing region set by the setting unit 121 from the depth information acquired by the depth acquisition unit 116 .

[0050] The determination unit 131 uses the depth information extracted by the extraction unit 130 to determine whether or not to use the image information of the subject in the matching process.

[0051] More specifically, the determination unit 131 obtains an unevenness level indicating the magnitude of unevenness in the processing region, using the depth information extracted by the extraction unit 130. Then, the determination unit 131 compares the obtained unevenness level with a predetermined unevenness standard to determine whether or not to use the image information of the subject in the matching process.

[0052] The unevenness level is an index showing the degree of unevenness in the processing region, and in this embodiment, is the standard deviation of the unevenness in the processing region.

[0053] The unevenness standard is set according to a general unevenness level when an actual person is photographed, and different standards are set according to the depth measurement accuracy.

[0054] For example, if the processing area when the measurement accuracy is low is the entire shooting area SA, the processing target includes the subject and its background. Therefore, the low-accuracy unevenness standard is set to a value according to the standard deviation of unevenness of the subject and its background when actually shooting a person (for example, the minimum value of the standard deviation of unevenness that generally occurs).

[0055] When the measurement accuracy is high, the processing area is a partial area including an area corresponding to the face of the subject. The high accuracy unevenness criterion is set to a value according to the standard deviation of unevenness in a typical human face (for example, the minimum value of the standard deviation of unevenness in a typical human face).

[0056] Referring again to FIG. The authentication unit 118 performs processing according to the result of the determination by the comparison and determination unit 117 .

[0057] In detail, when the matching judgment unit 117 judges that the image information of the subject is to be used for the matching process, the authentication unit 118 performs a person authentication process including a matching process of matching the image indicated by the image information with the read image M. In the person authentication process, for example, when the authenticity of the identification document is confirmed by the authentication process, it is further confirmed that the information input by the subject matches the contents of the identification document. Also, for example, in the person authentication process, the expiration date of the identification document may be confirmed, and these may be confirmed by an authenticator, and the result may be input to the support device 102.

[0058] When the matching judgment unit 117 judges that the image information of the subject will not be used in the matching process, the authentication unit 118 transmits a notification to that effect to the measurement device 101. As a result, the display unit 104 of the measurement device 101 displays a message indicating that the matching process will not be performed.

[0059] Up to this point, we have mainly explained the functional configuration of the person authentication support system 100. From now on, we will explain the physical configuration of the person authentication support system 100 with reference to the drawings.

[0060] <Physical configuration of the measuring device 101> 6, the measuring device 101 includes a bus 1010, a processor 1020, a memory 1030, a storage device 1040, a network interface 1050, a user interface 1060, a camera 1070, an illuminance sensor 1080, and a depth sensor 1090. Note that the measuring device 101 may be a personal computer to which the camera 1070, the illuminance sensor 1080, and the depth sensor 1090 are attached.

[0061] The bus 1010 is a data transmission path for transmitting and receiving data between the processor 1020, the memory 1030, the storage device 1040, the network interface 1050, the camera 1070, the illuminance sensor 1080, and the depth sensor 1090. However, the method of connecting the processor 1020 and the like to each other is not limited to bus connection.

[0062] The processor 1020 is implemented by a central processing unit (CPU) or a graphics processing unit (GPU).

[0063] The memory 1030 is a main storage device realized by a RAM (Random Access Memory) or the like.

[0064] The storage device 1040 is an auxiliary storage device realized by a hard disk drive (HDD), a solid state drive (SSD), a memory card, a read only memory (ROM), or the like. The storage device 1040 stores program modules for realizing each function of the measuring device 101. The processor 1020 loads each of these program modules onto the memory 1030, executes them, and cooperates with the network interface 1050, the user interface 1060, the camera 1070, the illuminance sensor 1080, and the depth sensor 1090 to realize each functional unit of the measuring device 101.

[0065] The network interface 1050 is an interface for communicating with the support device 102 via a network, and constitutes the communication unit 108 .

[0066] The user interface 1060 is a part that displays information to the user and allows the user to input information, and is composed of, for example, a liquid crystal panel, a touch sensor provided on the screen of the liquid crystal panel, a keyboard, a mouse, etc. The user interface 1060 constitutes the input unit 103 and the display unit 104.

[0067] The camera 1070 is a device that captures an image, and constitutes the reading unit 105. The illuminance sensor 1080 is a sensor that measures illuminance, and constitutes the brightness measurement unit 107. The depth sensor 1090 is a sensor that measures depth, and constitutes the depth measurement unit 106.

[0068] <Physical configuration of the person authentication support device 102> The person authentication support device 102 is physically, for example, a personal computer or a host machine for a server device, and includes a bus 2010, a processor 2020, a memory 2030, a storage device 2040, a network interface 2050, and a user interface 2060, as shown in FIG.

[0069] The bus 2010 is a data transmission path for transmitting and receiving data among the processor 2020, memory 2030, storage device 2040, network interface 2050, and user interface 2060. However, the method of connecting the processor 2020 and the like to each other is not limited to bus connection.

[0070] The processor 2020 is implemented by a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), or the like.

[0071] The memory 2030 is a main storage device realized by a RAM (Random Access Memory) or the like.

[0072] The storage device 2040 is an auxiliary storage device realized by a hard disk drive (HDD), a solid state drive (SSD), a memory card, a read only memory (ROM), or the like. The storage device 2040 stores program modules for realizing each function of the operated device 101. The processor 2020 loads each of these program modules onto the memory 2030, executes them, and cooperates with the network interface 2050 and the user interface 2060 as appropriate, thereby realizing each functional unit of the support device 102.

[0073] The network interface 2050 is an interface for communicating with the measuring device 101 via a network.

[0074] The user interface 2060 is a section for displaying information to the user and for allowing the user to input information, and is composed of, for example, a liquid crystal panel, a touch sensor provided on the screen of the liquid crystal panel, a keyboard, a mouse, and the like.

[0075] So far, we have explained the configuration of the person authentication support system 100. From now on, the operation of the person authentication support system 100 will be explained.

[0076] <Operation of the person authentication support system 100> In the person authentication support system 100, a measurement process is executed by a measurement device 101, and a person authentication support process is executed by a support device 102. The measurement process is a process for acquiring information (in this embodiment, image information, depth information, brightness information, and measurement condition information of the subject) used in the person authentication support process. The person authentication support process is a process for supporting person authentication of the subject.

[0077] These processes will be described below with reference to the drawings.

[0078] (Measurement processing) 8 is an example of a flowchart of a measurement process according to the first embodiment of the present invention. The measurement process is started, for example, by executing an application in the measurement device 101 and receiving a predetermined instruction from the subject.

[0079] The reading unit 105 reads the identification document by photographing the identification document in response to an instruction from the subject (step S101). As a result, the reading unit 105 generates read image information indicating the read image M.

[0080] The reading unit 105 photographs the photographing area SA in response to an instruction from the subject (step S102), and the display unit 104 displays the image of the photographing area SA photographed by the reading unit 105 (step S103). As a result, the photographing area SA photographed by the reading unit 105 is displayed on the display unit 104 in real time.

[0081] 9 is a diagram showing an example of an image displayed in step S103, and the image shows the shooting area SA shot in step S102. As shown in the figure, the image displayed in step S103 includes a guide G. The guide G indicates an appropriate range of the subject's face in the image. The position of the measuring device 101 may be adjusted so that the contour of the face generally coincides with the guide G.

[0082] The input unit 103 judges whether or not a predetermined photographing instruction has been received (step S104). Until a photographing instruction is input by the subject, the input unit 103 judges that the photographing instruction has not been received (step S104; No), and the reading unit 105 returns to the process of step S102.

[0083] If a photographing instruction is input by the subject and it is determined that the photographing instruction has been accepted (step S104; Yes), the reading unit 105 determines whether the position of the subject's face in the image of the photographing area SA is within a predetermined range (step S105).

[0084] When it is determined that the position of the face is not within a predetermined range (step S105; No), the reading unit 105 returns to the process of step S102.

[0085] If it is determined that the position of the face is within a predetermined range (step S105; Yes), the reading unit 105 captures an image of the shooting area SA (step S106). As a result, the reading unit 105 generates image information indicating an image of the shooting area SA. Fig. 10 shows an example of an image of the shooting area SA including the photographer's face, captured in step S106.

[0086] Subsequently, a measurement information generating process (step S107) is performed as shown in Fig. 8. Fig. 11 is a flowchart showing an example of the measurement information generating process (step S107).

[0087] The depth measurement unit 106 measures the depth of the imaging area SA imaged in step S106, and generates depth information indicating the measured depth (step S201).

[0088] 12 is a diagram showing an example of a plurality of measurement points MP determined in association with the photographing area SA. In the figure, the measurement points MP are shown as black circles, and are arranged at equal intervals vertically and horizontally. In step S201, the distance between the point in real space corresponding to the measurement point MP and the reading unit 105 is measured as the depth. In the figure, the image of the subject is shown by a dotted line so that the positional relationship between the subject photographed in step S106 and the measurement point MP can be seen.

[0089] In this embodiment, an example is described in which multiple measurement points MP are arranged vertically and horizontally at equal intervals, but the arrangement of the multiple measurement points MP is not limited to this, and the multiple measurement points MP may be arranged in any position.

[0090] Referring again to FIG. The brightness measurement unit 107 measures the brightness of the shooting environment when the shooting area SA is shot in step S106, and generates brightness information indicating the measured brightness (step S202).

[0091] The communication unit 108 acquires measurement condition information indicating the measurement conditions of the depth measured in step S201 from a storage unit (not shown) (step S203).

[0092] Referring again to FIG. The communication unit 108 transmits the brightness information, the read image information, the image information, the depth information, and the measurement condition information (step S108). The communication unit 108 transmits the brightness information, and when a request corresponding to the brightness information is received from the support device 102, the communication unit 108 transmits other information (the read image information, the image information, the measurement condition information, and the depth information).

[0093] The read image information transmitted in step S108 is generated by executing step S101. The image information transmitted in step S108 is generated by executing step S106. The depth information and brightness information transmitted in step S108 are generated in steps S201 and S202. The measurement condition information transmitted in step S108 is acquired in step S203.

[0094] As a result, the communication unit 108 ends the measurement process.

[0095] (Personal authentication support processing) 13 is an example of a flowchart of the person authentication support process according to the first embodiment of the present invention. The person authentication support process is started, for example, by the brightness acquisition unit 113 acquiring the brightness information transmitted in step S108. Hereinafter, the person authentication support process is also simply referred to as the "support process."

[0096] The matching and judging unit 117 judges whether or not the brightness indicated by the luminance information acquired by the luminance acquiring unit 113 satisfies the illuminance standard (step S301). If it is judged that the illuminance standard is not satisfied (step 301; No), the matching and judging unit 117 executes a notification process (step S302) to send a notification to the measuring device 101 that the matching process will not be performed, and ends the assistance process.

[0097] As described above, the illuminance standard is defined as a range including an upper limit and a lower limit, and the comparison / determination unit 117 determines that the illuminance standard is not satisfied if the illuminance is outside the range defined by the illuminance standard.

[0098] Generally, when the shooting environment is dark, the image of the image information becomes dark and the matching process may not be performed accurately. Therefore, when the value is less than the lower limit, the matching judgment unit 117 judges not to perform the matching process, notifies the user of the result, and ends the support process.

[0099] Also, if the shooting environment is bright, there is a possibility that the image displayed on the screen of a display or monitor has been shot. Therefore, if the upper limit value is exceeded, the matching judgment unit 117 judges not to perform matching processing, notifies the user to that effect, and ends the support processing.

[0100] If it is determined that the illuminance standard is satisfied (step 301; Yes), the comparison and judgment unit 117 transmits a predetermined request to the measurement device 101. In response to this request, the communication unit 108 transmits the read image information, image information, measurement condition information, and depth information. The read image acquisition unit 110, the image information acquisition unit 111, the measurement condition acquisition unit 112, and the depth acquisition unit 116 respectively acquire the read image information, the image information, the measurement condition information, and the depth information (step S303).

[0101] The accuracy determination unit 120 determines whether the depth measurement accuracy is high or not depending on whether the measurement accuracy obtained based on the measurement condition information and the measurement condition-accuracy data 114a acquired in step S303 satisfies a predetermined measurement standard (step S304).

[0102] In detail, the accuracy determining unit 120 obtains accuracy information associated with the measurement condition information obtained in step S303 in the measurement condition-accuracy data 114a. The accuracy determining unit 120 determines whether the depth measurement accuracy is high or not depending on whether the measurement accuracy indicated by the obtained accuracy information satisfies the measurement standard.

[0103] For example, when the measurement condition information acquired in step S303 indicates "A", the accuracy determining unit 120 acquires the accuracy information "150" associated with the measurement condition information "A" in the measurement condition-accuracy data 114a shown in Fig. 3. The accuracy determining unit 120 then compares the "150" indicated by the acquired accuracy information with a measurement standard. For example, when the measurement standard is that a value of 100 or more indicates high accuracy, the accuracy determining unit 120 determines that the depth measurement accuracy is high.

[0104] Furthermore, for example, if the measurement condition information acquired in step S303 indicates "B", the accuracy determining unit 120 acquires the accuracy information "80" associated with the measurement condition information "B" in the measurement condition-accuracy data 114a shown in Fig. 3. In the case of the above measurement standard, the accuracy determining unit 120 compares "150" indicated by the acquired accuracy information with the measurement standard, thereby determining that the depth measurement accuracy is low.

[0105] Referring again to FIG. If it is determined that the accuracy is not high (that is, the accuracy is low) (step S304; No), the setting unit 121 sets the entire shooting area SA of the image information acquired in step S303 as the processing area (step S305).

[0106] The matching judgment unit 117 determines whether or not to use the image information of the subject for the matching process, in other words, whether or not to perform matching process using the image information of the subject, based on the depth information of the entire shooting area SA, which is the processing area set in step S305 (step S306).

[0107] In detail, for example, the collation / determination unit 117 specifies the smallest one of the multiple measurement points MP included in the depth information of the entire imaging area SA as the reference depth. The collation / determination unit 117 obtains the unevenness of each of the measurement points MP included in the entire imaging area SA by subtracting the reference depth from each depth included in the depth information of the entire imaging area SA. The collation / determination unit 117 obtains the unevenness level of the entire imaging area SA by obtaining the standard deviation of the obtained unevenness.

[0108] The collation / determination unit 117 compares the obtained unevenness level with a low-precision unevenness reference, which is set to, for example, a minimum value of a general unevenness level in the entire shooting area SA where a person is actually shot.

[0109] Since the entire shooting area SA includes the subject and the background, the entire shooting area SA actually has some unevenness, whereas the screen of a display or monitor is generally flat. Therefore, the unevenness of the shooting area SA when actually shot usually has a larger variation than the unevenness when an image including a person displayed on the screen of a display or monitor is shot.

[0110] For this reason, if the obtained unevenness level is greater than the low-precision unevenness standard, it can be assumed that the image information is genuine (i.e., the image shown by the image information is the one that was actually photographed when the read image information was transmitted.) Therefore, if the obtained unevenness level is greater than the low-precision unevenness standard, the matching judgment unit 117 judges to perform matching processing using the image information of the subject.

[0111] On the other hand, if the obtained unevenness level is equal to or lower than the unevenness standard for low accuracy, the image information is presumed to be not authentic, and the matching judgment unit 117 decides not to perform matching processing using the image information of the subject.

[0112] When it is determined that the matching process using the image information of the subject is not to be performed (step S306; No), the matching determination unit 117 executes the above-mentioned notification process (step S302) and ends the assistance process.

[0113] When it is determined that the matching process using the image information of the subject is to be performed (step S306; Yes), the authentication unit 118 executes a person authentication process including the matching process (step S307), and ends the assistance process.

[0114] If it is determined that the accuracy is high (step S304; Yes), the setting unit 121 identifies a face area FR from the shooting area SA of the image information acquired in step S302, and sets the face area FR as the processing area (step S308).

[0115] FIG. 14 shows an example of a face area FR identified from the photographed area SA. The face area FR may be identified using a conventional image processing technique. For example, the conventional image processing technique may utilize image features contained in image information. For example, the conventional image processing technique may use a trained learning model for extracting the face area FR from an image including a face, and may output the face area FR by inputting an image including a face. Note that FIG. 14 shows an example in which the face area FR has an outer edge roughly following the contour of the face, and includes hair (head) but does not include clothing, but the face area FR may include one or both of the hair (head) and the neck, and may include the entire or part of clothing (for example, the collar near the face).

[0116] Referring again to FIG. The matching judgment unit 117 uses the depth information of the face area FR, which is the processing area set in step S308, to determine whether or not to use the image information of the subject for the matching process, in other words, whether or not to perform matching processing using the image information of the subject (step S309).

[0117] 15 is a diagram showing an example of measurement points MP included in the face region FR. In the drawing, the measurement points MP included in the face region FR are indicated by marks X. The depth information of the face region FR is information indicating the depth at the measurement points MP included in the face region FR.

[0118] In detail, for example, the collation / determination unit 117 specifies the minimum depth information of the measurement points MP included in the face area FR as the reference depth. The collation / determination unit 117 obtains the unevenness of each of the measurement points MP included in the face area FR by subtracting the reference depth from each depth included in the depth information of the face area FR. The collation / determination unit 117 obtains the unevenness level of the face area FR by obtaining a standard deviation of the obtained unevenness.

[0119] The collation / determination unit 117 compares the obtained unevenness level with a high-precision unevenness standard, which may be set to, for example, the minimum unevenness level of a typical human face.

[0120] A human face has bumps and grooves on the nose and surrounding areas, whereas the screen of a display or monitor is generally flat. Therefore, when a human face is actually photographed, the bumps and grooves usually vary more than when a photograph of a human face displayed on a display or monitor screen is taken.

[0121] For this reason, if the calculated unevenness level is greater than the high-precision unevenness standard, it can be assumed that the image information is genuine. Therefore, if the calculated unevenness level is greater than the high-precision unevenness standard, the matching judgment unit 117 judges that the image information of the subject should be used for matching processing.

[0122] On the other hand, if the obtained unevenness level is equal to or lower than the unevenness standard for high accuracy, the image information is presumed to be invalid, and the matching / determining unit 117 determines not to use the image information of the subject in the matching process.

[0123] Here, the authenticity of the image information (whether the image shown by the image information is an image that was actually captured) can be estimated based on the entire shooting area SA as well.

[0124] However, the entire shooting area SA includes not only the face area FR of the subject, but also areas other than the face area FR of the subject (areas of hair and clothing) and background areas other than the subject. Since the state of subjects' clothing and hair, and the state of the background are also various, the entire shooting area SA has relatively many uncertain factors that change depending on the shooting environment and conditions at the time of shooting. When authenticating image information using depth information of the entire shooting area SA, there is a risk that the authenticity of the image information cannot be accurately determined due to the influence of uncertain factors.

[0125] In contrast, the face area FR does not include the background and has fewer uncertain factors compared to the entire shooting area SA. Therefore, by verifying the authenticity of the image information using the depth information of the face area FR, which is a narrower area than the shooting area SA, it is more likely that the authenticity of the image information can be accurately determined without being affected by uncertain factors. However, since the face area FR usually has smaller irregularities than the entire shooting area SA, it is necessary to measure the depth under measurement conditions that allow measurement with high accuracy.

[0126] Therefore, as in this embodiment, when the measurement accuracy of the depth is determined to be high based on the measurement conditions, the authenticity of the image information can be accurately estimated by using the depth of the face area FR. On the other hand, when the measurement accuracy is determined to be low based on the measurement conditions, the authenticity of the image information can be accurately estimated by using the depth of the entire shooting area SA.

[0127] Here, as will be understood from the principle for estimating the authenticity of the image information described above, it is preferable that the processing area is an area corresponding to a portion with large concaves and convexes. Therefore, when the measurement accuracy is high, it is preferable to set the processing area including the area corresponding to the nose, and the above-mentioned face area FR is an example of a set area including the area corresponding to the nose. It is more preferable that the processing area is the nose and its surrounding area.

[0128] Referring again to FIG. When it is determined that the matching process using the image information of the subject is not to be performed (step S309; ​​No), the matching determination unit 117 executes the above-mentioned notification process (step S302) and ends the assistance process.

[0129] If it is determined that the matching process using the image information of the subject is to be performed (step S309; ​​Yes), the authentication unit 118 executes the person authentication process including the matching process (step S307), and ends the assistance process.

[0130] So far, the first embodiment of the present invention has been described.

[0131] According to this embodiment, the measurement conditions of depth are acquired in the measurement device 101 capable of generating image information showing an image of the photographing area SA including the face of the subject and depth information showing the depth. Then, a processing area, which is an area of ​​the photographing area SA to be processed for the depth information, is set according to the measurement conditions. When the depth information including the depth in the processing area measured under the above measurement conditions is acquired, it is determined whether or not to use the image information of the subject for the matching process using the depth information of the processing area.

[0132] As described in this embodiment, the authenticity of the image information can be accurately estimated by using depth information of different processing regions according to the measurement conditions. Then, by determining whether or not to use the image information of the subject in the matching process according to the estimation result of the authenticity of the image information, the matching process can be performed accurately, and the accuracy of person authentication can be improved. Therefore, it is possible to support the improvement of the accuracy of person authentication.

[0133] According to this embodiment, when the brightness measured by the brightness measuring unit 107 satisfies a predetermined illuminance standard, the depth information of the imaging area SA is acquired.

[0134] Depending on the brightness of the image or the shooting environment shown by the image information, it is possible to estimate whether the image included in the image information is suitable for matching processing or to estimate the authenticity of the image information, thereby helping to improve the accuracy of person authentication.

[0135] According to this embodiment, the illuminance criteria includes upper and lower brightness limits.

[0136] In a dark shooting environment, the image of the image information is often unclear. Therefore, by including a lower limit in the illuminance standard, it is possible to estimate whether the image included in the image information is suitable for matching processing.

[0137] In addition, in a bright shooting environment, an image displayed on a display or monitor may be photographed. Therefore, by including an upper limit in the illuminance standard, the authenticity of the image information can be estimated.

[0138] This makes it possible to help improve the accuracy of person authentication.

[0139] According to this embodiment, the measurement conditions are at least one of information for identifying a depth sensor that measures depth information, information for identifying an OS running on the measuring device 101, information for identifying a device equipped with the depth sensor, information for identifying an available API, and information for identifying a device adopted as the measuring device 101.

[0140] Such measurement conditions can be related to the measurement accuracy of the depth indicated by the depth information. By using the depth information of different processing regions according to such measurement conditions, the authenticity of the image information can be accurately estimated. Therefore, it is possible to support the improvement of the accuracy of person authentication.

[0141] According to this embodiment, it is determined whether the depth measurement accuracy is high or low based on the measurement conditions, and if the measurement accuracy is high, a narrower processing area is set than if the measurement accuracy is not high.

[0142] When the measurement accuracy is high, the authenticity of the image information can be accurately estimated by setting a narrow area with relatively few uncertain factors, such as the face area FR exemplified in this embodiment, as the processing area, which helps to improve the accuracy of person authentication.

[0143] According to this embodiment, the processing region when the measurement accuracy is high includes the region corresponding to the subject's nose.

[0144] The area corresponding to the nose is an area with relatively few uncertain factors and a relatively large amount of unevenness. By using such an area as the processing area for the case of high accuracy, the authenticity of the image information can be accurately estimated. Therefore, it is possible to support the improvement of the accuracy of person authentication.

[0145] According to the present embodiment, the depth information of the shooting area SA is acquired by the depth acquisition unit 116, and the depth information of the processing area is extracted from the acquired depth information. Then, based on the extracted depth information, it is determined whether or not to use the image information of the subject for the matching process.

[0146] This makes it possible to accurately estimate the authenticity of image information using depth information of different processing regions according to measurement conditions, thereby helping to improve the accuracy of person authentication.

[0147] According to this embodiment, the unevenness level indicating the magnitude of unevenness in the processing area is compared using the depth information of the processing area with a predetermined unevenness standard to determine whether or not to use the image information of the subject for the matching process.

[0148] By comparing the unevenness level with the unevenness standard using depth information of different processing areas according to the measurement conditions, the authenticity of the image information can be accurately estimated, thereby helping to improve the accuracy of person authentication.

[0149] <<Embodiment 2>> In the first embodiment, an example has been described in which the brightness measurement unit 107 generates brightness information, and when the brightness indicated by the brightness information satisfies the illuminance standard, the depth acquisition unit 116 acquires the depth information from the measurement device 101. However, the brightness measurement unit 107 does not have to be provided in the person authentication support system. In this case, the depth acquisition unit 116 only needs to acquire the depth information from the measurement device 101 regardless of the brightness of the shooting environment, etc.

[0150] <Configuration of person authentication support system 200> A person authentication support system 200 according to the second embodiment of the present invention is a system that supports person authentication of a subject, similar to the first embodiment. As shown in FIG. 16, the person authentication support system 200 includes a measurement device 201 and a person authentication support device 202.

[0151] The measurement device 201 does not include the brightness measurement unit 107, and the person authentication support device 202 does not include the brightness acquisition unit 113. Except for these points, the measurement device 201 and the person authentication support device 202 according to this embodiment may be configured functionally in the same manner as the measurement device 101 and the person authentication support device 102 according to the first embodiment, respectively.

[0152] Physically, the measuring device 201 according to this embodiment does not need to include the illuminance sensor 1080 (not shown). Except for this, the measuring device 201 and the person authentication support device 202 may be configured similarly to the measuring device 101 and the person authentication support device 102 according to the first embodiment, respectively.

[0153] <Operation of the person authentication support system 200> (Measurement processing) In the person authentication support system 200, a measurement device 201 executes a measurement process, and a support device 202 executes a person authentication support process.

[0154] 17 is an example of a flowchart of a measurement process according to the second embodiment of the present invention. As shown in the figure, in the measurement process according to this embodiment, the processes of steps S101 to S106 are executed similarly to those of the first embodiment. Then, instead of the measurement information generation process according to the first embodiment (step S107), a measurement information generation process (step S207) is executed.

[0155] 18 is a flowchart showing an example of the measurement information generation process (step S207). As shown in the figure, the measurement information generation process (step S207) according to this embodiment does not include the process of step S202 in the measurement information generation process (step S107) according to embodiment 1. That is, after the same processes as steps S201 and S203 according to embodiment 1 are executed, the communication unit 108 returns to the measurement process.

[0156] As shown in FIG. 17, the communication unit 108 transmits the read image information, image information, depth information, and measurement condition information (step S208), and ends the measurement process.

[0157] (Personal authentication support processing) 19 is an example of a flowchart of the person authentication support process according to the second embodiment of the present invention. As shown in the figure, in the person authentication support process according to the present embodiment, the process of step S301 according to the first embodiment is not executed. Except for this point, the person authentication support process according to the present embodiment is generally similar to the person authentication support process according to the first embodiment.

[0158] In this embodiment, the depth measurement conditions are acquired in the measuring device 101 capable of generating image information showing an image of the shooting area SA including the face of the subject and depth information showing the depth. Then, a processing area, which is an area of ​​the shooting area SA that is the target of processing of the depth information, is set according to the measurement conditions. When the depth information including the depth in the processing area measured under the above measurement conditions is acquired, it is determined whether to use the image information of the subject for the matching process based on the depth information of the processing area.

[0159] Therefore, similarly to the first embodiment, it is possible to help improve the accuracy of person authentication.

[0160] Moreover, according to the present embodiment, except for the effects related to the brightness and illuminance standard measured by the brightness measurement unit 107, other effects similar to those of the first embodiment are achieved.

[0161] Although one embodiment and a modification of the present invention have been described above with reference to the drawings, these are merely examples of the present invention and may be modified as appropriate.

[0162] (Modification 1: Modification of measurement condition information) In the embodiment, the measurement condition information is described as OS information. However, the measurement condition information is not limited to OS information, and may be, for example, depth sensor information, API information, device information, image information, environmental information, and depth information. Furthermore, the measurement condition information may be one or a combination of these exemplified pieces of information.

[0163] The depth sensor information is information for identifying the depth sensor constituting the depth measurement unit 106, and indicates, for example, the type of the depth sensor (manufacturer, model number, product number, etc.) and the measurement method of the depth sensor.

[0164] The API information is information for identifying available APIs (Application Programming Interfaces). An API is a function for utilizing the functions of the OS.

[0165] The device information is information for identifying the device employed as the measuring device 101, and indicates, for example, the type of the device (manufacturer, model number, product number, etc.) and the production date of the device.

[0166] The depth sensor information, API information, and device information may be stored in advance in a storage unit (not shown) included in the measurement device 101.

[0167] The environmental information is information that indicates the shooting environment of the image, and is, for example, brightness information.

[0168] This modification also provides the same effects as the embodiment.

[0169] (Modification 2: Modification of brightness information) In the embodiment, an example has been described in which the brightness information is generated by the brightness measurement unit 107. However, the brightness information may be information indicating the brightness of an image indicated by image information based on the image information, and in this case, the brightness information may be obtained based on the image information by, for example, the matching and judging unit 117 or the depth acquisition unit 116. In this case, the brightness information may be obtained by, for example, obtaining an average value of the brightness of each pixel included in the image information.

[0170] This modification also provides the same effects as the embodiment.

[0171] (Modification 3: Modification of measurement conditions-accuracy data and area setting section) In the embodiment, an example has been described in which the accuracy information of the measurement condition-accuracy data 114a indicates a value corresponding to the depth measurement accuracy, but the accuracy information may be any information indicating the depth measurement accuracy as described above.

[0172] For example, as shown in the measurement condition-accuracy data 114b in Fig. 20, the accuracy information may be set with information indicating whether the measurement accuracy is high or low, instead of the depth measurement accuracy. In this case, the region setting unit 115 does not need to include the accuracy determination unit 120, and may set the processing region according to the accuracy information associated with the measurement condition information in the measurement condition-accuracy data 114a.

[0173] This modification also provides the same effects as the embodiment.

[0174] (Modification 4: First Modification of Depth Acquisition Unit) In the first embodiment, an example has been described in which the depth acquisition unit 116 acquires the depth information of the imaging area SA when the brightness measured by the illuminance sensor satisfies the illuminance standard. However, the case in which the depth acquisition unit acquires the depth information of the imaging area SA is not limited to this.

[0175] For example, the depth acquisition unit may acquire the depth information of the imaging area SA when the brightness of the image indicated by the image information satisfies a predetermined illuminance standard. In this case, the brightness information is not necessary, so that the measurement device 101 does not need to include the brightness measurement unit 107, for example.

[0176] This modification also provides the same effects as the embodiment.

[0177] (Modification 5: Second Modification of Depth Acquisition Unit) In the embodiment, an example has been described in which the depth acquisition unit 116 acquires depth information indicating the depth of the entire shooting area SA from the measurement device 101. However, the depth acquisition unit may acquire depth information indicating the depth of only the processing area set by the area setting unit 115 from the measurement device 101. In this case, the matching determination unit may determine whether or not to use the image information of the subject for the matching process based on the depth information acquired by the depth acquisition unit.

[0178] This modification also provides the same effects as the embodiment.

[0179] (Modification 6: First modification of unevenness level) In the embodiment, the unevenness level has been described as the standard deviation of the unevenness in the processing region, but the unevenness level may be any index that indicates the degree of unevenness in the processing region. For example, the unevenness level may be the average value of the unevenness in the processing region, the maximum value of the difference between the unevenness, etc. In this case, the unevenness criterion may be set to a value that corresponds to the unevenness level.

[0180] In addition, the index used for the unevenness level is not limited to a continuous value, and may be a value, symbol, alphabet, etc. that indicates the degree of unevenness in stages. It is preferable that the unevenness standard be a value, symbol, alphabet, etc. that corresponds to the unevenness level so that it can be compared with the unevenness level.

[0181] This modification also provides the same effects as the embodiment.

[0182] (Modification 7: Second modification of unevenness level) In the embodiment, the unevenness level has been described as the standard deviation of the unevenness in the processing region, but as described above, the unevenness level may be any index that indicates the degree of unevenness in the processing region. The unevenness level is, for example, the maximum value of unevenness in a specific region in the processing region.

[0183] In this case, the specific area is an area in which the unevenness is larger than other areas in the processing area. For example, if the processing area in the case where the depth measurement accuracy is high is the face area FR, the specific area may be the nose area, which is generally an area in which the unevenness is larger than other areas in the face area FR. The nose area is the area around the nose.

[0184] The nose region may be identified using a conventional image processing technique. For example, the conventional image processing technique may utilize image features contained in the image information. For example, the conventional image processing technique may use a trained learning model for extracting the nose region from an image including a face, and may input an image including a face and output the nose region. For example, the nose region may be identified based on the size of the face region FR identified by the conventional image processing technique and the position of the eyes.

[0185] The unevenness level may be, for example, a value, a symbol, an alphabet, or the like, corresponding to the maximum unevenness in a specific region in the processing region. Furthermore, the unevenness level may be the depth itself or an index based on the depth itself, instead of an index based on the unevenness.

[0186] This modification also provides the same effects as the embodiment.

[0187] (Variation 8: Variation 1 of the configuration of the person authentication support system) An example has been described in which a person authentication support system 100 relating to an embodiment includes a measurement device 101 and a person authentication support device 102, the measurement device 101 including functional units 103 to 107, and the person authentication support device 102 including functional units 110 to 118 (see Figure 1).

[0188] However, it is sufficient that the person authentication support system as a whole includes the functional units 103-107 and 110-118, and for example, a measurement device may include some or all of the functional units 110-118.

[0189] Also, the person authentication support device 302 may include the functional units 103 to 107 included in the measurement device 101 according to the embodiment 1. Fig. 21 shows the configuration of a person authentication support system 300 according to the modification 8, which is one of such modifications.

[0190] The person authentication support system 300 includes a person authentication support device 302 and a server device 303. The person authentication support device 302 and the server device 303 are connected to each other via a network configured by a wired or wireless network or a suitable combination of these networks so as to be able to transmit and receive information to and from each other.

[0191] The person authentication support device 302 functionally includes an input unit 103, a display unit 104, a reading unit 105, a depth measurement unit 106, and a brightness measurement unit 107 similar to those in the first embodiment. The person authentication support device 302 functionally includes a read image acquisition unit 110, an image information acquisition unit 111, a measurement condition acquisition unit 112, a brightness acquisition unit 113, a data storage unit 114, a region setting unit 115, a depth acquisition unit 116, and a matching judgment unit 117 similar to those in the first embodiment.

[0192] However, each of the functional units 103 to 107 and 110 to 117 included in the person authentication support device 302 may output and obtain information to each other via an internal bus, instead of transmitting and receiving information via a network as in the embodiment.

[0193] The person authentication support device 302 further includes a communication unit 308 instead of the communication unit 108 according to the embodiment. The communication unit 308 transmits and receives information to and from the server device 303. The communication unit 308 according to this modification transmits image information and read image information to the server device 303, for example, in response to an instruction from the subject or when the processing in the person authentication support device 202 is completed.

[0194] The server device 303 includes the authentication unit 118 similar to that in the embodiment.

[0195] The person authentication support device 302 may have the physical configuration described with reference to Fig. 6. The server device 332 may have the physical configuration described with reference to Fig. 7.

[0196] Each functional unit of the person authentication support device 302 and the server device 303 may execute the same process as that executed by the corresponding functional unit in the first embodiment (i.e., the process described with reference to Figs. 8, 13, etc.). In this modification, the brightness measurement unit 107 and the brightness acquisition unit 113 may not be provided in the person authentication support device 302 as in the second embodiment.

[0197] This modification also provides the same effects as the embodiment.

[0198] (Modification 9: Modification 2 of the configuration of the person authentication support system) The person authentication support system may not include the measurement devices 101, 201 and the server device 303, and may be configured by a person authentication support device.

[0199] FIG. 22 is a diagram showing the functional configuration of a person authentication support device 402 according to the ninth modification.

[0200] As shown in the figure, the person authentication support device 402 according to this modification functionally includes an input unit 103, a display unit 104, a reading unit 105, a depth measurement unit 106, and a brightness measurement unit 107, which are the same as those in the first embodiment. The person authentication support device 402 also functionally includes a read image acquisition unit 110, an image information acquisition unit 111, a measurement condition acquisition unit 112, a brightness acquisition unit 113, a data storage unit 114, an area setting unit 115, a depth acquisition unit 116, a matching and judging unit 117, and an authentication unit 118.

[0201] The functional units 103-107 and 110-118 included in the person authentication support device 402 may output and obtain information to each other via an internal bus, instead of transmitting and receiving information via a network as in the embodiment. Therefore, the person authentication support device 402 may not include the communication unit 108 as shown in FIG.

[0202] The person authentication support device 402 may have the physical configuration described with reference to FIG.

[0203] Each functional unit of the person authentication support device 402 may execute the same process as that executed by the corresponding functional unit in the first embodiment (i.e., the process described with reference to Figs. 8, 13, etc.). In this modification, the brightness measurement unit 107 and the brightness acquisition unit 113 may not be provided in the person authentication support device 402 as in the second embodiment.

[0204] This modification also provides the same effects as the embodiment.

[0205] (Modification 10: Modification of the reading unit 105) For example, the reading unit 105 is not limited to a camera, but may be configured with a scanner or the like to read an identification document.

[0206] For example, the reading unit 105 may be configured to further include an OCR (Optical Character Reader) function, in which case, information for identifying the subject may be obtained from an image read from an identification document using the OCR function instead of being input by the subject.

[0207] Further, for example, the reading unit 105 may be a reader that reads information stored in an IC (Integrated Circuit) chip from the IC chip. In this case, the identification document may include an IC chip that previously stores information including the read image M, and the reading unit 105 may read information from the IC chip of the identification document. The IC chip may further store information for identifying the subject, and in this case, the information for identifying the subject may be obtained by reading information from the IC chip instead of being input by the subject.

[0208] Furthermore, in the diagrams showing the flow used in the above description, multiple steps (processing) are described in order, but the order of execution of these steps is not limited to the order described. The order of these steps may be changed as long as it does not cause any problems in terms of content. In addition, the above-mentioned embodiment and modified examples may be combined as long as the content is not contradictory.

[0209] One or all of the above-described embodiments can be described as, but are not limited to, the following supplementary notes.

[0210] 1. A measurement condition acquisition means for acquiring a measurement condition of a depth in a measurement device capable of generating image information showing an image of a shooting area including a face of a subject and depth information showing a depth; a region setting means for setting a processing region, which is a region to be processed for the depth information, within the photographing region in accordance with the measurement conditions; a depth acquisition means for acquiring depth information including a depth in the processing region measured under the measurement conditions; a matching determination means for determining whether or not to use the image information of the subject for matching processing based on the depth information of the processing area. Identity authentication support system. 2. The depth acquisition means acquires the depth information of the imaging area when the brightness of the image indicated by the image information satisfies a predetermined illuminance standard. The person authentication support system described in 1 above. 3. The depth acquisition means acquires the depth information of the imaging area when the brightness measured by the illuminance sensor satisfies a predetermined illuminance standard. The person authentication support system described in 1 above. 4. The illuminance standard includes upper and lower limits of the brightness. 3. A person authentication support system according to claim 2 or 3 above. 5. The measurement conditions are at least one of information for identifying a depth sensor that measures the depth information, information for identifying an operating system that runs on the measurement device, information for identifying a device equipped with the depth sensor, information for identifying an available API, and information for identifying a device employed as the measurement device. 5. A person authentication support system according to any one of 1 to 4 above. 6. The area setting means an accuracy determining means for determining whether or not the measurement accuracy of the depth is high based on the measurement conditions; and a setting means for setting a processing area narrower when the measurement accuracy is high than when the measurement accuracy is not high. 6. A person authentication support system according to any one of 1 to 5 above. 7. When the measurement accuracy is high, the processing area includes an area corresponding to the subject's nose. 6. A person authentication support system as described above in claim 6. 8. The depth acquisition means acquires depth information of the processing area set by the setting means; The matching determination means determines whether or not to use the image information of the subject for matching processing based on the depth information acquired by the depth acquisition means. 8. The person authentication support system according to claim 6 or 7. 9. The depth acquisition means acquires depth information of the imaging area; The collation and determination means an extraction means for extracting depth information of the processing region set by the setting means from the depth information acquired by the depth acquisition means; and a determination means for determining whether or not to use the image information of the subject in a matching process based on the depth information extracted by the extraction means. 8. The person authentication support system according to claim 6 or 7. 10. The matching judgment means judges whether or not to use the image information of the subject for matching processing by comparing an unevenness level indicating the magnitude of unevenness in the processing area using the depth information of the processing area with a predetermined unevenness standard. 10. A person authentication support system according to any one of 1 to 9 above. 11. A measuring device capable of generating image information indicating an image of a photographed area including a face of a subject and depth information indicating a depth; A measurement condition acquisition means for acquiring a depth measurement condition of the measuring device; a region setting means for setting a processing region, which is a region to be processed for the depth information, within the photographing region in accordance with the measurement conditions; a matching determination means for determining whether or not to use the image information of the subject for matching processing based on the depth information of the processing area. Identity authentication support device. 12. The computer Acquiring a depth measurement condition in a measurement device capable of generating image information indicating an image of a shooting area including a face of a subject and depth information indicating a depth; Setting a processing area, which is an area to be processed of the depth information, in the shooting area according to the measurement conditions; acquiring depth information including a depth in the processing region measured under the measurement conditions; A method for supporting person authentication, comprising determining whether or not to use image information of the subject for matching processing based on depth information of the processing area. 13. On the computer, Acquiring a depth measurement condition in a measurement device capable of generating image information indicating an image of a shooting area including a face of a subject and depth information indicating a depth; Setting a processing area, which is an area to be processed of the depth information, in the shooting area according to the measurement conditions; acquiring depth information including a depth in the processing region measured under the measurement conditions; and determining whether or not to use image information of the subject for the matching process based on depth information of the processing area. [Explanation of symbols]

[0211] 100,200,300 Identity authentication support system 101,201 Measuring equipment 102,202,302 Person authentication support device 103 Input section 104 Display section 105 Reading unit 106 Depth measurement section 107 Brightness measurement section 108,308 Communications Department SA Shooting Area MP measurement point 110 Image acquisition unit 111 Image information acquisition unit 112 Measurement condition acquisition unit 113 Brightness acquisition part 114 Data storage unit 114a, 114b Measurement conditions - accuracy data 115 Area setting section 116 Depth acquisition part 117 Matching and Judging Department 118 Authentication Department 120 Accuracy judgment section 121 Setting section 130 Extraction part 131 Judgment Department FR Face area 332 Server device

Claims

1. obtaining information regarding the accuracy of the depth measurement; obtaining depth information from a range corresponding to information on the depth measurement accuracy; A process of matching a person based on the depth information; A program that causes a computer to execute the following.

2. The program according to claim 1, When the measurement accuracy based on the information on the measurement accuracy is low, the depth information is obtained from a second range that is wider than a first range that is set when the measurement accuracy based on the information on the measurement accuracy is high. program.

3. The program according to claim 2, The first range includes a face region of the person. program.

4. The program according to claim 2, The second range includes an area other than the face area of ​​the person. program.

5. The program according to claim 1, The information regarding the depth measurement accuracy includes measurement condition information. program.

6. obtaining information regarding the accuracy of the depth measurement; obtaining depth information from a range corresponding to information on the depth measurement accuracy; A process of matching a person based on the depth information; An information processing method implemented by a computer.

7. 7. An information processing method according to claim 6, When the measurement accuracy based on the information on the measurement accuracy is low, the depth information is obtained from a second range that is wider than a first range that is set when the measurement accuracy based on the information on the measurement accuracy is high. Information processing methods.

8. 8. An information processing method according to claim 7, The first range includes a face region of the person. Information processing methods.

9. 8. An information processing method according to claim 7, The second range includes an area other than the face area of ​​the person. Information processing methods.

10. 7. An information processing method according to claim 6, The information regarding the depth measurement accuracy includes measurement condition information. Information processing methods.

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