Information processing device, information processing method, and recording medium

Abstract

An information processing device (10) comprises: a deterioration degree calculation means (110) that calculates the degree of deterioration in quality of an image; a deterioration cause classification means (120) that classifies a deterioration cause that is the cause of deterioration in quality of the image; and a quality score calculation means (130) that calculates a quality score indicating the quality of the image on the basis of the deterioration degree and the deterioration cause. The information processing device can evaluate the quality of an image appropriately.

Description

[Technical Field]

[0001] The present disclosure relates to the technical fields of an information processing device, an information processing method, and a recording medium. [Background technology]

[0002] Known devices of this type evaluate the quality of images of an object. For example, Patent Document 1 discloses a technique for segmenting eye images and estimating their quality using a convolutional neural network. Patent Document 2 discloses a technique for identifying the cause of image degradation that caused the deterioration of image quality when evaluating the image quality of eye images.

[0003] As another related technique, for example, Patent Document 3 discloses generating weight information from the quality of a plurality of pieces of imaging data. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Japanese Patent Publication No. 2020-144926 [Patent Document 2] Japanese Patent Application Laid-Open No. 2005-071009 [Patent Document 3] International Publication No. 2021 / 176544 Summary of the Invention [Problem to be solved by the invention]

[0005] This disclosure aims to improve upon the techniques disclosed in the prior art documents. [Means for solving the problem]

[0006] One aspect of the information processing device disclosed herein comprises a degradation degree calculation means for calculating the degree of quality degradation in an image, a degradation factor classification means for classifying degradation factors that are factors that cause the quality of the image to deteriorate, and a quality score calculation means for calculating a quality score that indicates the quality of the image based on the degradation degree and the degradation factors.

[0007] One aspect of the information processing method disclosed herein involves using at least one computer to calculate the degree of quality degradation in an image, classifying the degradation factors that caused the quality degradation of the image, and calculating a quality score that indicates the quality of the image based on the degree of degradation and the degradation factors.

[0008] One aspect of the recording medium of this disclosure is a recording medium having recorded thereon a computer program that causes at least one computer to execute an information processing method, which calculates the degree of quality degradation in an image, classifies the degradation factors that caused the quality degradation of the image, and calculates a quality score that indicates the quality of the image based on the degree of degradation and the degradation factors. [Brief explanation of the drawings]

[0009] [Figure 1] 1 is a block diagram showing a hardware configuration of an information processing device according to a first embodiment. [Figure 2] 1 is a block diagram showing a functional configuration of an information processing device according to a first embodiment. [Figure 3] 4 is a flowchart showing the flow of operations of the information processing device according to the first embodiment. [Figure 4] FIG. 10 is a block diagram showing the functional configuration of an information processing device according to a second embodiment. [Figure 5] 10 is a flowchart showing the flow of operations of the information processing device according to the second embodiment. [Figure 6] FIG. 2 is a block diagram showing a configuration related to learning of a weight setting unit. [Figure 7] 10 is a flowchart showing the flow of a learning operation of a weight setting unit. [Figure 8]10 is a flowchart showing the flow of operations of the information processing device according to the third embodiment. [Figure 9] 10 is a flowchart showing the flow of operations of the information processing device according to the fourth embodiment. [Figure 10] FIG. 11 is a block diagram showing the functional configuration of an information processing device according to a fifth embodiment. [Figure 11] FIG. 13 is a block diagram showing the functional configuration of an information processing device according to a sixth embodiment. [Figure 12] 13 is a flowchart showing the flow of operations of the information processing device according to the sixth embodiment. [Figure 13] FIG. 13 is a block diagram showing the functional configuration of an information processing device according to a seventh embodiment. [Figure 14] 13 is a flowchart showing the flow of operations of the information processing device according to the seventh embodiment. [Figure 15] 13 is a flowchart showing the flow of authentication operations performed by an information processing device according to the eighth embodiment. [Figure 16] 13 is a flowchart showing the flow of authentication operations performed by an information processing device according to the ninth embodiment. [Figure 17] FIG. 20 is a block diagram showing the functional configuration of an information processing device according to a tenth embodiment. [Figure 18] 13 is a flowchart showing the flow of operations of the information processing device according to the tenth embodiment. [Figure 19] 22 is a flowchart showing the flow of operations of the information processing device according to the eleventh embodiment. [Figure 20] 22 is a flowchart showing the flow of operations of the information processing device according to the twelfth embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0010] Hereinafter, embodiments of an information processing device, an information processing method, and a recording medium will be described with reference to the drawings.

[0011] First Embodiment An information processing apparatus according to a first embodiment will be described with reference to FIGS.

[0012] (Hardware configuration) First, the hardware configuration of the information processing device according to the first embodiment will be described with reference to Fig. 1. Fig. 1 is a block diagram showing the hardware configuration of the information processing device according to the first embodiment.

[0013] 1, an information processing device 10 according to the first embodiment includes a processor 11, a RAM (Random Access Memory) 12, a ROM (Read Only Memory) 13, and a storage device 14. The information processing device 10 may further include an input device 15 and an output device 16. The processor 11, RAM 12, ROM 13, storage device 14, input device 15, and output device 16 are connected to each other via a data bus 17.

[0014] The processor 11 loads a computer program. For example, the processor 11 is configured to load a computer program stored in at least one of the RAM 12, the ROM 13, and the storage device 14. Alternatively, the processor 11 may load a computer program stored in a computer-readable storage medium using a storage medium reading device (not shown). The processor 11 may acquire (i.e., load) the computer program from a device (not shown) located outside the information processing device 10 via a network interface. The processor 11 controls the RAM 12, the storage device 14, the input device 15, and the output device 16 by executing the loaded computer program. In particular, in this embodiment, when the processor 11 executes the loaded computer program, a functional block for calculating a quality score of an image is realized within the processor 11. In other words, the processor 11 may function as a controller that executes each control in the information processing device 10.

[0015] The processor 11 may be configured as, for example, a central processing unit (CPU), a graphics processing unit (GPU), a field-programmable gate array (FPGA), a demand-side platform (DSP), or an application-specific integrated circuit (ASIC). The processor 11 may be configured as one of these, or may be configured to use multiple processors in parallel.

[0016] The RAM 12 temporarily stores computer programs executed by the processor 11. The RAM 12 temporarily stores data that the processor 11 temporarily uses while the processor 11 is executing the computer programs. The RAM 12 may be, for example, a dynamic random access memory (DRAM) or a static random access memory (SRAM). Alternatively, other types of volatile memory may be used instead of the RAM 12.

[0017] The ROM 13 stores computer programs executed by the processor 11. The ROM 13 may also store fixed data. The ROM 13 may be, for example, a P-ROM (Programmable Read Only Memory) or an EPROM (Erasable Read Only Memory). Alternatively, other types of non-volatile memory may be used instead of the ROM 13.

[0018] The storage device 14 stores data that the information processing device 10 stores for a long period of time. The storage device 14 may operate as a temporary storage device for the processor 11. The storage device 14 may include, for example, at least one of a hard disk device, a magneto-optical disk device, an SSD (Solid State Drive), and a disk array device.

[0019] The input device 15 is a device that receives input instructions from a user of the information processing device 10. The input device 15 may include, for example, at least one of a keyboard, a mouse, and a touch panel. The input device 15 may be configured as a mobile terminal such as a smartphone or a tablet. The input device 15 may also be, for example, a device that includes a microphone and is capable of voice input.

[0020] The output device 16 is a device that outputs information related to the information processing device 10 to the outside. For example, the output device 16 may be a display device (e.g., a display) that can display information related to the information processing device 10. The output device 16 may also be a speaker or the like that can output information related to the information processing device 10 as audio. The output device 16 may be configured as a mobile terminal such as a smartphone or a tablet. The output device 16 may also be a device that outputs information in a format other than an image. For example, the output device 16 may be a speaker that outputs information related to the information processing device 10 as audio.

[0021] 1 shows an example of information processing device 10 configured to include multiple devices, but all or some of the functions may be realized as a single device. In that case, information processing device 10 may be configured to include only processor 11, RAM 12, and ROM 13 described above, and other components (i.e., storage device 14, input device 15, output device 16) may be provided in an external device connected to information processing device 10. Furthermore, some of the calculation functions of information processing device 10 may be realized by an external device (e.g., an external server, a cloud, etc.).

[0022] (Functional configuration) Next, the functional configuration of the information processing device 10 according to the first embodiment will be described with reference to Fig. 2. Fig. 2 is a block diagram showing the functional configuration of the information processing device according to the first embodiment.

[0023] 2, the information processing device 10 according to the first embodiment is configured to include, as components for realizing its functions, a deterioration degree calculation unit 110, a deterioration factor classification unit 120, and a quality score calculation unit 130. Each of the deterioration degree calculation unit 110, the deterioration factor classification unit 120, and the quality score calculation unit 130 may be a processing block realized by, for example, the above-mentioned processor 11 (see FIG. 1). Furthermore, the deterioration degree calculation unit 110, the deterioration factor classification unit 120, and the quality score calculation unit 130 may each be configured as a neural network.

[0024] The degradation degree calculation unit 110 is configured to calculate the degree of degradation of an image. The "degree of degradation" here indicates the degree of degradation of the image quality. The specific method for calculating the degree of degradation is not particularly limited. For example, the degradation degree calculation unit 110 may calculate the degree of degradation using feature points extracted from an image. More specifically, the degree of eye opening may be calculated as the degree of degradation using iris feature points extracted from an iris image. The "degree of eye opening" here is a value indicating the degree to which the eyes are open, and may be calculated as a value where, for example, a closed eye state (a state in which the eyes are completely closed) is 0% and an open eye state (a state in which the eyes are fully open) is 100%. Alternatively, the degradation degree calculation unit 110 may input an image to a pre-trained neural network and obtain the degree of degradation as its output. The degree of degradation may include multiple indicators that are causes of degradation of image quality.

[0025] The degradation factor classification unit 120 is configured to be able to classify the degradation factors of an image. The degradation factor classification unit 120 may be configured to select an appropriate degradation factor as the degradation factor of an image from, for example, a plurality of degradation factors prepared in advance. More specifically, the degradation factor classification unit 120 may be configured to output a degradation factor label indicating the type of degradation factor and a degradation factor label likelihood indicating the likelihood of each degradation factor. The degradation factor label and the degradation factor label likelihood may be obtained as the output of a pre-trained neural network when an image is input.

[0026] The types of degradation factors are not particularly limited, but for example, degradation factors of iris images used in iris authentication can be classified into blur degradation, occlusion degradation, and other degradation. More specifically, blur degradation may include focus blur, motion blur, etc. Occlusion degradation may include squinting, eyeglass reflection occlusion, iris intra-reflection occlusion, eyeglass frame occlusion, out-of-frame, pupil size change, eyelash occlusion, bangs occlusion, etc. Other degradation may include insufficient resolution, oblique light, contact lenses, off-angle, sensor noise, etc.

[0027] The quality score calculation unit 130 is configured to be able to calculate a quality score of an image. More specifically, the quality score calculation unit 130 is configured to be able to calculate a quality score based on the degree of degradation calculated by the degradation degree calculation unit 110 and the degradation factors classified by the degradation factor classification unit 120. Therefore, the quality score in this embodiment is calculated as an integrated score that takes into account both the degree of degradation of an image and the degradation factors. The quality score calculation unit 130 may be configured to input the degree of degradation, the degradation factor label, and the degradation factor label likelihood to a pre-trained neural network and obtain the quality score as a result.

[0028] (Operation flow) Next, the flow of operations of the information processing device 10 according to the first embodiment (specifically, the flow up to calculating the quality score of an image) will be described with reference to Fig. 3. Fig. 3 is a flowchart showing the flow of operations of the information processing device according to the first embodiment.

[0029] 3, when the operation of the information processing device 10 according to the first embodiment is started, first, each of the deterioration degree calculation unit 110 and the deterioration factor classification unit 120 acquires an image for calculating a quality score (step S101). The image may be directly captured by a camera, or may be stored in a storage device or the like.

[0030] Next, the deterioration degree calculation unit 110 calculates the deterioration degree of the acquired image (step S102). Furthermore, the deterioration factor classification unit 120 classifies the deterioration factor of the acquired image (step S103). Note that the processes of steps S102 and S103 may be executed in tandem or simultaneously in parallel.

[0031] Next, the quality score calculation unit 130 calculates a quality score based on the degree of deterioration calculated by the deterioration degree calculation unit 110 and the deterioration factors classified by the deterioration factor classification unit 120 (step S104). Then, the quality score calculation unit 130 outputs the calculated quality score (step S105). The output destination and usage method of the quality score will be described in detail in other embodiments described later.

[0032] (Technical Effects) Next, the technical effects obtained by the information processing device 10 according to the first embodiment will be described.

[0033] 1 to 3, the information processing device 10 according to the first embodiment calculates a quality score based on the degree of image degradation and the degradation factors. In this way, both the degree of degradation and the degradation factors are taken into consideration, so a more appropriate quality score can be calculated compared to, for example, a case where the quality score is calculated based only on the degree of image degradation. In other words, it is possible to more appropriately evaluate the quality of the image.

[0034] Second Embodiment An information processing device 10 according to the second embodiment will be described with reference to Figures 4 to 7. The second embodiment differs from the first embodiment described above only in part of the configuration and operation, and other parts may be the same as the first embodiment. Therefore, the following will describe in detail the parts that differ from the first embodiment already described, and will omit a description of other overlapping parts as appropriate.

[0035] (Functional configuration) First, the functional configuration of the information processing device 10 according to the second embodiment will be described with reference to Fig. 4. Fig. 4 is a block diagram showing the functional configuration of the information processing device according to the second embodiment. Note that in Fig. 4, the same elements as those shown in Fig. 2 are denoted by the same reference numerals.

[0036] As shown in Fig. 4, the information processing device 10 according to the second embodiment is configured to include, as components for realizing its functions, a deterioration degree calculation unit 110, a deterioration factor classification unit 120, a quality score calculation unit 130, and a weight setting unit 140. That is, the information processing device 10 according to the second embodiment further includes the weight setting unit 140 in addition to the configuration of the first embodiment (see Fig. 2). The weight setting unit 140 may be a processing block realized by, for example, the above-mentioned processor 11 (see Fig. 1).

[0037] The weight setting unit 140 is configured to be able to set weights (e.g., weight coefficients) used when calculating the quality score. More specifically, the weight setting unit 140 is configured to be able to set weights corresponding to at least one of the deterioration degrees calculated by the deterioration degree calculation unit 110 and the deterioration factors classified by the deterioration factor classification unit 120. For example, when the deterioration degree calculation unit 110 calculates multiple deterioration degrees using multiple indexes, the weight setting unit 140 may set weights corresponding to each of the multiple deterioration degrees. Furthermore, for example, when the deterioration factor classification unit 120 outputs multiple deterioration factors, the weight setting unit 140 may set weights corresponding to each of the multiple deterioration factors. A more specific method of setting weights will be described in detail in another embodiment described later.

[0038] (Operation flow) Next, the flow of operations of the information processing device 10 according to the second embodiment will be described with reference to Fig. 5. Fig. 5 is a flowchart showing the flow of operations of the information processing device according to the second embodiment. Note that in Fig. 5, the same processes as those shown in Fig. 3 are denoted by the same reference numerals.

[0039] 5, when the operation of the information processing device 10 according to the second embodiment is started, first, each of the deterioration degree calculation unit 110 and the deterioration factor classification unit 120 acquires an image for which a quality score is to be calculated (step S101). Then, the deterioration degree calculation unit 110 calculates the deterioration degree of the acquired image (step S102). Furthermore, the deterioration factor classification unit 120 classifies the deterioration factor of the acquired image (step S103).

[0040] Next, weight setting unit 140 sets weights to be used in calculating the quality score (step S201). After that, quality score calculation unit 130 calculates a quality score based on the degree of deterioration calculated by deterioration degree calculation unit 110 and the deterioration factors classified by deterioration factor classification unit 120, using the weights set by weight setting unit 140 (step S202). Then, quality score calculation unit 130 outputs the calculated quality score (step S105).

[0041] (Study configuration) Next, a configuration related to learning of the weight setting section 140 will be described with reference to Fig. 6. Fig. 6 is a block diagram showing a configuration related to learning of the weight setting section.

[0042] 6, the weight setting unit 140 may set weights using a pre-trained model (such as a neural network). The weight setting unit 140 may be trained using the loss function calculation unit 210, the gradient calculation unit 220, and the parameter update unit 230. Each of the loss function calculation unit 210, the gradient calculation unit 220, and the parameter update unit 230 may be a processing block realized by, for example, the above-mentioned processor 11 (see FIG. 1).

[0043] The loss function calculation unit 210 is configured to be able to calculate a preset loss function. More specifically, the loss function calculation unit 210 is configured to be able to calculate a loss function based on the weights set by the weight setting unit 140 and an input evaluation score. The evaluation score here is a score for evaluating the weights set by the weight setting unit 140, and is correct answer data corresponding to the input during learning. The evaluation score may be, for example, a score used for comparison to determine how appropriate the weights set by the weight setting unit 140 are.

[0044] The gradient calculation unit 220 is configured to be able to calculate the gradient of the loss function calculated by the loss function calculation unit 210. The gradient of the loss function is a value that indicates the slope of a graph of the loss function, and may be a value calculated by, for example, the "backpropagation method." The gradient calculation unit 220 may calculate the gradient of the loss function by, for example, differentiating the loss function.

[0045] The parameter update unit 230 is configured to be able to update the parameters (i.e., parameters used when setting weights) of the weight setting unit 140. More specifically, the parameter update unit 230 is configured to update the parameters of the weight setting unit 140 using the gradient calculated by the gradient calculation unit 220 so as to minimize the loss function.

[0046] (Learning behavior) Next, the operation when learning the weight setting section 140 (hereinafter referred to as "learning operation") will be described with reference to Fig. 7. Fig. 7 is a flowchart showing the flow of the learning operation of the weight setting section.

[0047] 7, when the learning operation of the weight setting unit 140 starts, first, the weight setting unit 140 sets weights corresponding to the degree of deterioration and the deterioration factor (step S251). Then, the loss function calculation unit 210 calculates a loss function using the quality score calculated using the weight set by the weight setting unit 140 and the evaluation score corresponding to the learning input (step S252).

[0048] Next, the gradient calculation unit 220 calculates the gradient of the loss function calculated by the loss function calculation unit 210 (step S253). After that, the parameter update unit 230 uses the gradient calculated by the gradient calculation unit 220 to update the parameters of the weight setting unit 140 so that the loss function is minimized (step S254).

[0049] Next, the information processing device 10 determines whether learning has ended (step S255). Whether learning has ended may be determined, for example, according to a predetermined number of iterations. If it is determined that learning has not ended (step S255: NO), the process is repeated again from step S251. If it is determined that learning has ended (step S255: YES), the series of operations ends.

[0050] The above-described learning method is an example, and other methods may be used for learning by the weight setting unit 140. Learning by the weight setting unit 140 may be performed before the information processing device 10 is actually operated, or may be performed during operation (i.e., while calculating the quality score of an image).

[0051] (Technical Effects) Next, the technical effects obtained by the information processing device 10 according to the second embodiment will be described.

[0052] As described with reference to FIGS. 4 to 7, in the information processing device 10 according to the second embodiment, the quality score of an image is calculated using weights set by the weight setting unit 140. In this way, it is possible to adjust the influence of the degree of degradation and the degradation factors on the quality score and calculate a more appropriate quality score. For example, different authentication devices (authentication engines) have different robustness against degradation factors (for example, there are authentication devices that are robust against blur and authentication devices that are robust against occlusion). Therefore, if the factors of quality degradation can be estimated, it is possible to calculate a quality score that suits the characteristics of the authentication device.

[0053] Third Embodiment An information processing device 10 according to the third embodiment will be described with reference to Fig. 8. Note that the third embodiment differs from the second embodiment described above only in some of its operations, and other parts may be the same as the first and second embodiments. Therefore, the following will describe in detail the parts that differ from the embodiments already described, and will omit a description of other overlapping parts as appropriate.

[0054] (Operation flow) First, the flow of operations of the information processing device 10 according to the third embodiment will be described with reference to Fig. 8. Fig. 8 is a flowchart showing the flow of operations of the information processing device according to the third embodiment. Note that in Fig. 8, the same processes as those shown in Fig. 5 are denoted by the same reference numerals.

[0055] 8, when the operation of the information processing device 10 according to the third embodiment is started, first, each of the deterioration degree calculation unit 110 and the deterioration factor classification unit 120 acquires an image for which a quality score is to be calculated (step S101). Then, the deterioration degree calculation unit 110 calculates the deterioration degree of the acquired image (step S102). Furthermore, the deterioration factor classification unit 120 classifies the deterioration factor of the acquired image (step S103).

[0056] Next, the weight setting unit 140 acquires information about an output destination to which at least one of the image and the quality score is output (hereinafter referred to as "output destination information" as appropriate) (step S301). The output destination information may include, for example, information about a device to which the quality score is output, information about the use of the quality score at the output destination, etc. For example, if the quality score is output to an authentication device that performs authentication processing, the output destination information may include information about the authentication device that is the output destination, and information about the authentication processing performed by the authentication device.

[0057] Next, the weight setting unit 140 sets weights based on the acquired output destination information (step S302). The weight setting unit 140 sets weights so that processing at the output destination is performed more appropriately, for example. For example, when the image and quality score are output to an authentication device to perform authentication processing, the weight setting unit 140 sets weights so as to maximize the performance of the authentication device.

[0058] Next, the quality score calculation unit 130 calculates a quality score based on the degree of deterioration calculated by the deterioration degree calculation unit 110 and the deterioration factors classified by the deterioration factor classification unit 120, using the weights set by the weight setting unit 140 (here, the weights set based on the output destination information) (step S202). Then, the quality score calculation unit 130 outputs the calculated quality score (step S105).

[0059] (Technical Effects) Next, the technical effects obtained by the information processing device 10 according to the third embodiment will be described.

[0060] As described in FIG. 8, in the information processing device 10 according to the third embodiment, weights are set when calculating the quality score based on the output destination to which at least one of the image and the quality score is output. This makes it possible to calculate a quality score according to the intended use of the output destination. For example, when comparing the intended use of an iris image used for iris authentication (i.e., the intended use of registering a registered image for matching) with the intended use of authentication (i.e., the intended use of matching against the registered image), a low-quality image in the registered image can lead to false acceptance, so the intended use of registration requires higher quality than the intended use of authentication. As in this example, the required authentication accuracy and security level may differ depending on the intended use of the output destination. In this embodiment, an appropriate quality score can be calculated according to such differences in intended use.

[0061] <Fourth embodiment> An information processing device 10 according to the fourth embodiment will be described with reference to Fig. 9. Note that the fourth embodiment differs from the second and third embodiments described above only in some of its operations, and other parts may be the same as the first to third embodiments. Therefore, the following will describe in detail the parts that differ from the embodiments already described, and will omit a description of other overlapping parts as appropriate.

[0062] (Operation flow) First, the flow of operations of the information processing device 10 according to the fourth embodiment will be described with reference to Fig. 9. Fig. 9 is a flowchart showing the flow of operations of the information processing device according to the fourth embodiment. Note that in Fig. 9, the same processes as those shown in Fig. 5 are denoted by the same reference numerals.

[0063] 9, when the operation of the information processing device 10 according to the fourth embodiment is started, first, each of the deterioration degree calculation unit 110 and the deterioration factor classification unit 120 acquires an image for which a quality score is to be calculated (step S101). Then, the deterioration degree calculation unit 110 calculates the deterioration degree of the acquired image (step S102). Furthermore, the deterioration factor classification unit 120 classifies the deterioration factor of the acquired image (step S103).

[0064] Next, the weight setting unit 140 acquires information about the environment in which the image is captured (hereinafter referred to as "imaging environment information" as appropriate) (step S401). The imaging environment information may include, for example, information about the camera that captures the image, information about the location where the image is captured, information about the subject to be captured, etc. For example, the imaging environment information may include information about various camera parameters (e.g., exposure, etc.). Alternatively, the imaging environment information may include information about the brightness of the location where the image is captured or the time of day when the image is captured. Alternatively, the imaging environment information may include information about the size, height, moving speed, etc. of the subject to be captured. The imaging environment information may be acquired (collected) by the weight setting unit 140 itself, for example, or may be collected by a separately provided imaging environment information collecting unit or the like and stored in a database, and then read out by the weight setting unit 140 as appropriate.

[0065] Next, the weight setting unit 140 sets weights based on the acquired imaging environment information (step S402). The weight setting unit 140 may set weights taking into consideration, for example, factors of deterioration that may occur in the current imaging environment. For example, in an imaging environment where blur degradation is likely to occur, the weight setting unit 140 may set a larger weight corresponding to blur degradation.

[0066] Next, the quality score calculation unit 130 calculates a quality score based on the degree of deterioration calculated by the deterioration degree calculation unit 110 and the deterioration factors classified by the deterioration factor classification unit 120, using the weights set by the weight setting unit 140 (here, the weights set based on the imaging environment information) (step S202). Then, the quality score calculation unit 130 outputs the calculated quality score (step S105).

[0067] (Technical Effects) Next, the technical effects obtained by the information processing device 10 according to the fourth embodiment will be described.

[0068] 9, in the information processing device 10 according to the fourth embodiment, the weights are changed depending on the environment in which the image is captured. In this way, it is possible to calculate an appropriate quality score depending on the capturing environment.

[0069] The third and fourth embodiments may be combined. That is, the weight setting unit 140 may set weights based on both the output destination information and the imaging environment information. Furthermore, the weight setting unit 140 may set weights using other information in addition to the output destination information and the imaging environment information.

[0070] Fifth Embodiment An information processing device 10 according to the fifth embodiment will be described with reference to Fig. 10. The fifth embodiment differs only in part of the configuration from the first to fourth embodiments described above, and other parts may be the same as the first to fourth embodiments. Therefore, the following will describe in detail the parts that differ from the embodiments already described, and will omit a description of other overlapping parts as appropriate.

[0071] (Functional configuration) First, the functional configuration of the information processing device 10 according to the fifth embodiment will be described with reference to Fig. 10. Fig. 10 is a block diagram showing the functional configuration of the information processing device according to the fifth embodiment. Note that in Fig. 10, the same elements as those shown in Fig. 2 are denoted by the same reference numerals.

[0072] As shown in Fig. 10, the information processing device 10 according to the fifth embodiment is configured to include, as components for realizing its functions, a plurality of degradation degree calculation units 110, a degradation factor classification unit 120, and a quality score calculation unit 130. That is, the information processing device 10 according to the fifth embodiment differs from the configuration of the first embodiment (see Fig. 2) in that a plurality of degradation degree calculation units 110 is provided. Note that, for convenience of explanation, in Fig. 10, the plurality of degradation degree calculation units 110 are illustrated as degradation degree calculation units A, B, C, ..., but the number of degradation degree calculation units 110 is not particularly limited. For example, two, three, or more degradation degree calculation units 110 may be provided.

[0073] The plurality of degradation degree calculation units 110 are configured to calculate the degradation degree using different indices, respectively. Therefore, the degradation degrees calculated by the plurality of degradation degree calculation units 110 may be different from one another. For example, the plurality of degradation degree calculation units 110 may be configured to calculate degradation degrees corresponding to different preset degradation factors. More specifically, the degradation degree calculation unit A may calculate a blur score (e.g., a score corresponding to degradation due to at least one of focus blur and motion blur), while the degradation degree calculation unit B may calculate an area score (e.g., a score corresponding to the effective area of ​​the imaging target (e.g., iris)).

[0074] The multiple degrees of deterioration calculated by the multiple deterioration degree calculation units 110 are output to the quality score calculation unit 130. Then, the quality score calculation unit 130 according to this embodiment calculates a quality score based on the multiple degrees of deterioration and the deterioration factors. Note that the weight setting unit 140 described in the second to fourth embodiments may be provided. In this case, the weight setting unit 140 may set a weight for each of the multiple deterioration degree calculation units 110. For example, the weight setting unit 140 may set a weight coefficient corresponding to each of the deterioration degree calculation units A, B, and C.

[0075] (Technical Effects) Next, the technical effects obtained by the information processing device 10 according to the fifth embodiment will be described.

[0076] As described with reference to FIG. 10 , in the information processing device 10 according to the fifth embodiment, multiple deterioration degrees are calculated by multiple deterioration degree calculation units 110. This allows for a more appropriate quality score to be calculated compared to using only one deterioration degree. For example, by using the deterioration degree calculated for each deterioration factor, a quality score can be calculated that takes into account the influence of each deterioration factor. Furthermore, by additionally calculating the deterioration degree for a deterioration factor of interest, the deterioration degree for the deterioration factor of interest can be estimated in detail, allowing for more accurate calculation of the quality score. For example, if it is desired to more accurately estimate whether the eyes are wide open, this can be achieved by including the deterioration degree related to the eye opening degree in multiple deterioration degree calculation units 110.

[0077] Sixth Embodiment An information processing device 10 according to the sixth embodiment will be described with reference to Figures 11 and 12. The sixth embodiment differs only in part of the configuration and operation from the first to fifth embodiments described above, and other parts may be the same as the first to fifth embodiments. Therefore, the following will describe in detail the parts that differ from the embodiments already described, and will omit a description of other overlapping parts as appropriate.

[0078] (Functional configuration) First, the functional configuration of the information processing device 10 according to the sixth embodiment will be described with reference to Fig. 11. Fig. 11 is a block diagram showing the functional configuration of the information processing device according to the sixth embodiment. In Fig. 11, the same elements as those shown in Fig. 2 are denoted by the same reference numerals.

[0079] 11, the information processing device 10 according to the sixth embodiment is configured to include, as components for realizing its functions, a deterioration degree calculation unit 110, a deterioration factor classification unit 120, a quality score calculation unit 130, and a deterioration degree determination unit 150. That is, the information processing device 10 according to the sixth embodiment further includes, in addition to the configuration of the first embodiment (see FIG. 2), a deterioration degree determination unit 150. The deterioration degree determination unit 150 may be a processing block realized by, for example, the above-mentioned processor 11 (see FIG. 1).

[0080] The deterioration degree determination unit 150 is configured to be able to determine whether the degree of deterioration calculated by the deterioration degree calculation unit 110 is equal to or greater than a predetermined threshold. The "predetermined threshold" here is set as a threshold for determining whether the degree of image deterioration is large enough to determine that the deterioration factor should be classified. For example, the predetermined threshold may be set as a threshold for determining whether the degree of image deterioration is high enough to affect authentication processing using a quality score. The determination result of the deterioration degree determination unit 150 is configured to be output to the deterioration factor classification unit 120.

[0081] (Operation flow) Next, the flow of operations of the information processing device 10 according to the sixth embodiment will be described with reference to Fig. 12. Fig. 12 is a flowchart showing the flow of operations of the information processing device according to the sixth embodiment. Note that in Fig. 12, the same processes as those shown in Fig. 3 are denoted by the same reference numerals.

[0082] 12, when the operation of the information processing device 10 according to the sixth embodiment starts, first, each of the deterioration degree calculation unit 110 and the deterioration factor classification unit 120 acquires an image for which a quality score is to be calculated (step S101). Then, the deterioration degree calculation unit 110 calculates the deterioration degree of the acquired image (step S102).

[0083] Next, the deterioration degree determination unit 150 determines whether the deterioration degree calculated by the deterioration degree calculation unit 110 is greater than a predetermined threshold value (step S601). If it is determined that the deterioration degree is greater than the predetermined threshold value (step S601: YES), the deterioration factor classification unit 120 classifies the deterioration factors of the acquired image (step S103). Thereafter, the quality score calculation unit 130 calculates a quality score based on the deterioration degree calculated by the deterioration degree calculation unit 110 and the deterioration factors classified by the deterioration factor classification unit 120 (step S104). Then, the quality score calculation unit 130 outputs the calculated quality score (step S105).

[0084] On the other hand, if it is determined that the degree of deterioration is not greater than the predetermined threshold (step S601: NO), the deterioration factor classification unit 120 does not classify the deterioration factor of the acquired image (i.e., the processing of step S103 is omitted). In this case, the quality score calculation unit 130 calculates a quality score based only on the degree of deterioration calculated by the deterioration degree calculation unit 110 (step S602). Then, the quality score calculation unit 130 outputs the quality score calculated based only on the degree of deterioration (step S105).

[0085] In this way, in the information processing device 10 according to the sixth embodiment, whether or not to classify the deterioration factors is determined depending on whether or not the deterioration degree is greater than a predetermined threshold. Note that, in the above example, when the deterioration factors are not classified, the quality score is calculated based only on the deterioration degree, but when the deterioration factors are not classified, the quality score may not be calculated.

[0086] (Technical Effects) Next, the technical effects obtained by the information processing device 10 according to the sixth embodiment will be described.

[0087] 11 and 12, in the information processing device 10 according to the sixth embodiment, the cause of deterioration is classified when the degree of deterioration exceeds a predetermined threshold. In this way, the processing load required for classifying the cause of deterioration can be reduced compared to when the cause of deterioration is always classified.

[0088] Seventh Embodiment An information processing device 10 according to the seventh embodiment will be described with reference to Figures 13 and 14. The seventh embodiment differs only in part of the configuration and operation from the first to sixth embodiments described above, and other parts may be the same as the first to sixth embodiments. Therefore, the following will describe in detail the parts that differ from the embodiments already described, and will omit a description of other overlapping parts as appropriate.

[0089] (Functional configuration) First, the functional configuration of the information processing device 10 according to the seventh embodiment will be described with reference to Fig. 13. Fig. 13 is a block diagram showing the functional configuration of the information processing device according to the seventh embodiment. In Fig. 13, the same elements as those shown in Fig. 2 are denoted by the same reference numerals.

[0090] 13, the information processing device 10 according to the seventh embodiment is configured to include, as components for realizing its functions, a deterioration degree calculation unit 110, a deterioration factor classification unit 120, a quality score calculation unit 130, and an authentication unit 160. That is, the information processing device 10 according to the seventh embodiment further includes the authentication unit 160 in addition to the configuration of the first embodiment (see FIG. 2). The authentication unit 160 may be a processing block realized by, for example, the above-mentioned processor 11 (see FIG. 1).

[0091] The authentication unit 160 is configured to be able to perform authentication processing using an image. The type of authentication processing performed by the authentication unit 160 is not particularly limited, and may be, for example, iris authentication using an iris image or face authentication using a face image. In this case, the authentication unit 160 may determine whether or not to authenticate by comparing the image to a registered image. Furthermore, the authentication unit 160 according to this embodiment uses the quality score calculated by the quality score calculation unit 130 in addition to the image in the authentication processing. The authentication unit 160 may use the quality score to output the authentication result (i.e., to determine whether or not to authenticate), or may use the quality score to evaluate the authentication result. For example, when an authentication result, such as authentication failure, is found, the authentication unit 160 may use the quality score to determine whether the failure was due to a decrease in image quality. Alternatively, the authentication unit 160 may use the quality score as a measure of reliability for the authentication result (for example, when the authentication score is low despite a high quality score, or when there is a high possibility that registered data does not exist). However, how the authentication unit 160 uses the quality score in the authentication processing is not limited to the above example. Other methods of using the quality score in the authentication process will be described in detail in other embodiments below.

[0092] (Operation flow) Next, the flow of operations of the information processing device 10 according to the seventh embodiment will be described with reference to Fig. 14. Fig. 14 is a flowchart showing the flow of operations of the information processing device according to the seventh embodiment. Note that in Fig. 14, the same processes as those shown in Fig. 3 are denoted by the same reference numerals.

[0093] 14, when the operation of the information processing device 10 according to the seventh embodiment is started, first, each of the deterioration degree calculation unit 110 and the deterioration factor classification unit 120 acquires an image for which a quality score is to be calculated (particularly, an image used in authentication processing here) (step S101). Then, the deterioration degree calculation unit 110 calculates the deterioration degree of the acquired image (step S102). Furthermore, the deterioration factor classification unit 120 classifies the deterioration factor of the acquired image (step S103).

[0094] Next, the quality score calculation unit 130 calculates a quality score based on the degree of deterioration calculated by the deterioration degree calculation unit 110 and the deterioration factors classified by the deterioration factor classification unit 120 (step S104). The quality score calculated by the quality score calculation unit 130 is output to the authentication unit 160.

[0095] Next, the authentication unit 160 performs authentication processing based on the image and the quality score (step S701). That is, in the authentication processing performed by the authentication unit 160, not only the image itself but also the quality score of the image (in other words, the degree of degradation of the image and the factors of degradation) are taken into consideration.

[0096] (Technical Effects) Next, the technical effects obtained by the information processing device 10 according to the seventh embodiment will be described.

[0097] 13 and 14, the information processing device 10 according to the seventh embodiment executes authentication processing using an image and a quality score. In this way, the quality score of the image is also taken into consideration in the authentication processing, so that more appropriate authentication processing can be executed compared to when only an image is used.

[0098] Eighth Embodiment An information processing device 10 according to the eighth embodiment will be described with reference to Fig. 15. The eighth embodiment describes a specific example of the authentication operation (i.e., the operation of the authentication unit 160) in the seventh embodiment described above, and other parts may be the same as those in the first to seventh embodiments. Therefore, the following will describe in detail parts that differ from the embodiments already described, and will omit explanations of other overlapping parts as appropriate.

[0099] (Authentication operation) First, the flow of authentication operations performed by the information processing device 10 according to the eighth embodiment will be described with reference to Fig. 15. Fig. 15 is a flowchart showing the flow of authentication operations performed by the information processing device according to the eighth embodiment.

[0100] 15, when the authentication operation by the information processing device 10 according to the eighth embodiment is started, the authentication unit 160 first acquires an image and a quality score (step S801). Then, the authentication unit 160 determines whether the quality score is higher than a predetermined score (step S802). The "predetermined score" here is set as a threshold value for determining whether the quality score is high enough to properly execute the authentication process.

[0101] If the quality score is higher than the predetermined score (step S802: YES), the authentication unit 160 compares the acquired image with a registered image (step S803) and outputs the authentication result (step S804). That is, depending on the image comparison result, it outputs whether the authentication was successful or failed.

[0102] On the other hand, if the quality score is lower than the predetermined score (step S802: NO), the authentication unit 160 does not execute the authentication process (i.e., the processes of steps S803 and S804 are omitted). In this case, the authentication unit 160 may output a result indicating that the authentication has failed. Alternatively, the authentication unit 160 may output information instructing the user to recapture the image.

[0103] (Technical Effects) Next, the technical effects obtained by the information processing device 10 according to the eighth embodiment will be described.

[0104] 15, in the information processing device 10 according to the eighth embodiment, image matching is performed when the quality score is higher than a predetermined score. In this way, it is possible to prevent a decrease in the accuracy of the authentication process due to matching being performed using an image of low quality.

[0105] Ninth Embodiment An information processing device 10 according to the ninth embodiment will be described with reference to Fig. 16. Note that, like the eighth embodiment described above, the ninth embodiment describes a specific example of the authentication operation in the seventh embodiment, and other parts may be the same as the first to eighth embodiments. Therefore, the following will describe in detail parts that differ from the embodiments already described, and will omit explanations of other overlapping parts as appropriate.

[0106] (Authentication operation) First, the flow of authentication operations performed by the information processing device 10 according to the ninth embodiment will be described with reference to Fig. 16. Fig. 16 is a flowchart showing the flow of authentication operations performed by the information processing device according to the ninth embodiment. Note that in Fig. 16, the same processes as those shown in Fig. 15 are denoted by the same reference numerals.

[0107] 16, when the authentication operation by the information processing device 10 according to the ninth embodiment is started, the authentication unit 160 first acquires an image and a quality score (step S801). Then, the authentication unit 160 acquires a matching score by comparing the acquired image with a registered image (step S901). The matching score here may indicate, for example, the degree of match between the acquired image and the registered image.

[0108] Next, the authentication unit 160 determines the authentication result using the quality score and the matching score (step S903) and outputs the authentication result (step S804). For example, the authentication unit 160 may perform a determination based on the quality score and a determination based on the matching score separately, and determine that the authentication is successful if the conditions are met in both determinations. Alternatively, the authentication unit 160 may calculate an integrated score for authentication using the quality score and the matching score, and determine the authentication result using the integrated score for authentication.

[0109] (Technical Effects) Next, the technical effects obtained by the information processing device 10 according to the ninth embodiment will be described.

[0110] 16, in the information processing device 10 according to the ninth embodiment, the result of the authentication process (e.g., whether the authentication is successful or unsuccessful) is determined using both the quality score and the matching score. In this way, by using the quality score, the degree of degradation and the cause of degradation are taken into consideration in the authentication process, and therefore it is possible to improve the accuracy of the authentication process compared to when the result of the authentication process is determined using only the matching score (e.g., the degree of image match).

[0111] Tenth Embodiment An information processing device 10 according to the tenth embodiment will be described with reference to Figures 17 and 18. The tenth embodiment differs from the seventh embodiment described above only in part of its configuration and operation, and other parts may be the same as the first to ninth embodiments. Therefore, the following will describe in detail the parts that differ from the embodiments already described, and will omit a description of other overlapping parts as appropriate.

[0112] (Functional configuration) First, the functional configuration of the information processing device 10 according to the tenth embodiment will be described with reference to Fig. 17. Fig. 17 is a block diagram showing the functional configuration of the information processing device according to the tenth embodiment. In Fig. 17, the same elements as those shown in Fig. 13 are denoted by the same reference numerals.

[0113] 17, the information processing device 10 according to the tenth embodiment is configured to include, as components for realizing its functions, a deterioration degree calculation unit 110, a deterioration factor classification unit 120, a quality score calculation unit 130, an authentication unit 160, and an image registration unit 170. That is, the information processing device 10 according to the tenth embodiment further includes an image registration unit 170 in addition to the configuration of the tenth embodiment (see FIG. 13). The image registration unit 170 may be a processing block realized by, for example, the above-mentioned processor 11 (see FIG. 1).

[0114] The image registration unit 170 is configured to be able to register a registration image used in the authentication process by the authentication unit 160. The image registration unit 170 may register the registration image in, for example, the above-mentioned storage device 14 (see FIG. 1). Alternatively, the image registration unit 170 may register the registration image in a storage device external to the device. Furthermore, the image registration unit 170 according to this embodiment is particularly configured to determine whether or not the registration image can be registered based on the quality score calculated by the quality score calculation unit 130. For example, the image registration unit 170 may register the acquired image as a registration image when the quality score exceeds a preset registrable score.

[0115] (Operation flow) Next, the flow of operations of the information processing device 10 according to the tenth embodiment will be described with reference to Fig. 18. Fig. 18 is a flowchart showing the flow of operations of the information processing device according to the tenth embodiment. Note that in Fig. 18, the same processes as those shown in Fig. 3 are denoted by the same reference numerals.

[0116] 18, when the operation of the information processing device 10 according to the tenth embodiment is started, first, each of the deterioration degree calculation unit 110 and the deterioration factor classification unit 120 acquires an image for which a quality score is to be calculated (particularly, an image to be registered as a registered image) (step S101). Then, the deterioration degree calculation unit 110 calculates the deterioration degree of the acquired image (step S102). Furthermore, the deterioration factor classification unit 120 classifies the deterioration factor of the acquired image (step S103).

[0117] Next, the quality score calculation unit 130 calculates a quality score based on the degree of deterioration calculated by the deterioration degree calculation unit 110 and the deterioration factors classified by the deterioration factor classification unit 120 (step S104). The quality score calculated by the quality score calculation unit 130 is output to the image registration unit 170.

[0118] Next, the image registration unit 170 determines whether the quality score is higher than the registration score (step S1001). If the quality score is higher than the registration score (step S1001: YES), the image registration unit 170 registers the acquired image as a registered image (step S1002). On the other hand, if the quality score is lower than the registration score (step S1001: NO), the image registration unit 170 does not register the acquired image as a registered image (i.e., the processing of step S1002 is omitted). In this case, information instructing to acquire (capture) a new image may be output.

[0119] (Technical Effects) Next, the technical effects obtained by the information processing device 10 according to the tenth embodiment will be described.

[0120] 17 and 18, the information processing device 10 according to the tenth embodiment determines whether or not an image can be registered based on the quality score. This makes it possible to prevent a decrease in the accuracy of the authentication process due to an image of poor quality being registered.

[0121] Eleventh Embodiment An information processing device 10 according to the eleventh embodiment will be described with reference to Fig. 19. The eleventh embodiment differs from the seventh embodiment described above only in some of its operations, and other parts may be the same as the first to tenth embodiments. Therefore, the following will describe in detail the parts that differ from the embodiments already described, and will omit a description of other overlapping parts as appropriate.

[0122] (Operation flow) First, the flow of operations of the information processing device 10 according to the 11th embodiment will be described with reference to Fig. 19. Fig. 19 is a flowchart showing the flow of operations of the information processing device according to the 11th embodiment. Note that in Fig. 19, the same processes as those shown in Fig. 14 are denoted by the same reference numerals.

[0123] 19, when the operation of the information processing device 10 according to the eleventh embodiment is started, first, each of the deterioration degree calculation unit 110 and the deterioration factor classification unit 120 acquires an image for which a quality score is to be calculated (particularly, an image used in authentication processing here) (step S101). Then, the deterioration degree calculation unit 110 calculates the deterioration degree of the acquired image (step S102). Furthermore, the deterioration factor classification unit 120 classifies the deterioration factor of the acquired image (step S103).

[0124] Next, the quality score calculation unit 130 calculates a quality score based on the degree of deterioration calculated by the deterioration degree calculation unit 110 and the deterioration factors classified by the deterioration factor classification unit 120 (step S104). The quality score calculated by the quality score calculation unit 130 is output to the authentication unit 160.

[0125] Next, the authentication unit 160 performs authentication processing based on the image and the quality score (step S701). Then, the authentication unit 160 according to this embodiment particularly outputs the authentication result and the degradation factor (step S1101). That is, the authentication unit 160 outputs the degradation factor classified by the degradation factor classification unit 120 in addition to information indicating whether the authentication processing was successful or unsuccessful.

[0126] The authentication result and the deterioration factor may be output using, for example, the output device 16 (see FIG. 1). More specifically, the authentication result and the deterioration factor may be displayed as images using a display or the like. Alternatively, the authentication result and the deterioration factor may be output as audio using a speaker or the like. The authentication result and the deterioration factor may be output in different ways. For example, the authentication result may be displayed as an image using a display or the like, while the deterioration factor may be output as audio using a speaker or the like. The authentication result and the deterioration factor may be output simultaneously or at different times.

[0127] (Technical Effects) Next, the technical effects obtained by the information processing device 10 according to the eleventh embodiment will be described.

[0128] 19, the information processing device 10 according to the eleventh embodiment outputs the cause of image degradation in addition to the authentication result. In this way, the cause of image degradation can be communicated to the user of the device. Therefore, for example, when retaking an image, it is possible to appropriately inform the user of the problem of what needs to be improved, such as how to improve the image quality.

[0129] <Twelfth embodiment> An information processing device 10 according to the twelfth embodiment will be described with reference to Fig. 20. The twelfth embodiment differs from the eleventh embodiment in some of its operations, and other parts may be the same as the first to eleventh embodiments. Therefore, the following will describe in detail the parts that differ from the embodiments already described, and will omit a description of other overlapping parts as appropriate.

[0130] (Operation flow) First, the flow of operations of the information processing device 10 according to the 12th embodiment will be described with reference to Fig. 20. Fig. 20 is a flowchart showing the flow of operations of the information processing device according to the 12th embodiment. Note that in Fig. 20, the same processes as those shown in Fig. 14 are denoted by the same reference numerals.

[0131] 20, when the operation of the information processing device 10 according to the twelfth embodiment is started, each of the deterioration degree calculation unit 110 and the deterioration factor classification unit 120 acquires an image for which a quality score is to be calculated (particularly, an image used in authentication processing here) (step S101). Then, the deterioration degree calculation unit 110 calculates the deterioration degree of the acquired image (step S102). Furthermore, the deterioration factor classification unit 120 classifies the deterioration factor of the acquired image (step S103).

[0132] Next, the quality score calculation unit 130 calculates a quality score based on the degree of deterioration calculated by the deterioration degree calculation unit 110 and the deterioration factors classified by the deterioration factor classification unit 120 (step S104). The quality score calculated by the quality score calculation unit 130 is output to the authentication unit 160.

[0133] Next, the authentication unit 160 executes authentication processing based on the image and the quality score (step S701). Then, the authentication unit 160 according to this embodiment particularly calculates the degree of influence on the authentication result for each degradation factor (step S1201). Specifically, the authentication unit 160 calculates the degree of influence on the authentication result for each degradation factor classified by the degradation factor classification unit 120. Note that existing technology can be appropriately adopted as a specific method for calculating the degree of influence.

[0134] Next, the authentication unit 160 outputs the authentication result and the degradation factors that have a high impact on the authentication process (step S1202). That is, the authentication unit 160 changes the output mode of the degradation factors output along with the authentication result depending on the impact of the degradation factors. For example, the authentication unit 160 may output only those degradation factors that exceed a predetermined value among the multiple degradation factors. Alternatively, the authentication unit 160 may extract and output a predetermined number of degradation factors from the multiple degradation factors in descending order of impact. Alternatively, the authentication unit 160 may change the display mode of the degradation factors depending on the impact. For example, degradation factors with a high impact may be highlighted (e.g., displayed in a conspicuous color or large letters), while degradation factors with a low impact may be displayed normally. Alternatively, degradation factors with a low impact may be displayed in a less conspicuous manner (e.g., displayed in a lighter color).

[0135] (Technical Effects) Next, the technical effects obtained by the information processing device 10 according to the twelfth embodiment will be described.

[0136] As described in FIG. 20, in the information processing device 10 according to the 12th embodiment, of the image degradation factors, those that have a high impact on the authentication result are output. In this way, it is possible to more appropriately notify items that need to be improved compared to when all degradation factors are output in the same way. Furthermore, by notifying the impact of degradation factors on the authentication process, the characteristics of the authentication unit 160 can be clarified. Furthermore, quality can be improved efficiently. For example, if only degradation factors that have a high impact on the authentication process are improved, it may not be necessary to improve degradation factors that have a low impact (i.e., sufficient authentication accuracy can be obtained without improving all degradation factors).

[0137] The scope of each embodiment also includes a processing method in which a program that operates the configuration of each embodiment to realize the functions of the above-described embodiments is recorded on a recording medium, the program recorded on the recording medium is read as code, and the program is executed on a computer. In other words, a computer-readable recording medium is also included in the scope of each embodiment. Furthermore, each embodiment includes not only a recording medium on which the above-described program is recorded, but also the program itself.

[0138] Examples of recording media that can be used include floppy disks, hard disks, optical disks, magneto-optical disks, CD-ROMs, magnetic tapes, non-volatile memory cards, and ROMs. Furthermore, the scope of each embodiment is not limited to programs that execute processing by themselves, but also includes programs that execute processing by operating on an OS in cooperation with other software or functions of an expansion board. Furthermore, the program itself may be stored on a server, and part or all of the program may be downloadable from the server to a user terminal.

[0139] <Additional Notes> The above-described embodiment may be further described as follows, but is not limited to the following.

[0140] (Appendix 1) The information processing device described in Appendix 1 is an information processing device that includes a degradation degree calculation means that calculates the degree of quality degradation in an image, a degradation factor classification means that classifies degradation factors that are the factors that cause the quality of the image to deteriorate, and a quality score calculation means that calculates a quality score that indicates the quality of the image based on the degradation degree and the degradation factors.

[0141] (Appendix 2) The information processing device described in Appendix 2 is the information processing device described in Appendix 1, further comprising a weight setting means for setting a weight corresponding to at least one of the degree of deterioration and the deterioration factor, and the quality score calculation means calculates the quality score based on the degree of deterioration, the deterioration factor, and the weight.

[0142] (Appendix 3) The information processing device according to Supplementary Note 3 is the information processing device according to Supplementary Note 2, wherein the weight setting means sets the weight based on information relating to an output destination to which at least one of the image and the quality score is output.

[0143] (Appendix 4) The information processing device according to Supplementary Note 4 is the information processing device according to Supplementary Note 2 or 3, wherein the weight setting means changes the weight depending on an environment when the image is captured.

[0144] (Appendix 5) The information processing device according to Supplementary Note 5 is the information processing device according to any one of Supplementary Notes 1 to 4, wherein the deterioration degree calculation means calculates a plurality of degrees of deterioration using a plurality of indexes different from each other.

[0145] (Appendix 6) The information processing device described in Appendix 6 is an information processing device described in any one of Appendixes 1 to 5, further comprising a deterioration degree determination means for determining whether the deterioration degree is higher than a predetermined threshold, and the deterioration factor classification means classifies the deterioration factor when it is determined that the deterioration degree is higher than the predetermined threshold.

[0146] (Appendix 7) The information processing device described in Supplementary Note 7 is the information processing device described in any one of Supplementary Notes 1 to 6, further comprising an authentication means that uses the image and the quality score to perform authentication processing on an object contained in the image.

[0147] (Appendix 8) The information processing device described in Appendix 8 is the information processing device described in Appendix 7, wherein the authentication means determines whether the authentication process can be executed based on the quality score, and executes the authentication process if it is determined that the process can be executed.

[0148] (Appendix 9) The information processing device described in Appendix 9 is the information processing device described in Appendix 7 or 8, wherein the authentication means calculates a matching score from the image and outputs a result of the authentication processing based on the matching score and the quality score.

[0149] (Appendix 10) The information processing device described in Appendix 10 is an information processing device described in any one of Appendixes 7 to 9, further comprising an image registration means for registering a registration image to be used in the authentication process, and the image registration means determines whether or not the registration image can be registered based on the quality score.

[0150] (Appendix 11) The information processing device according to Supplementary Note 11 is the information processing device according to any one of Supplementary Notes 7 to 10, wherein the authentication means outputs the cause of deterioration together with a result of the authentication process.

[0151] (Appendix 12) The information processing device described in Appendix 12 is the information processing device described in Appendix 11, wherein the authentication means calculates the impact on the authentication process for each degradation factor and outputs the degradation factor according to the level of the impact.

[0152] (Appendix 13) The information processing method described in Appendix 13 is an information processing method that calculates the degree of quality degradation in an image using at least one computer, classifies the degradation factors that caused the quality degradation of the image, and calculates a quality score that indicates the quality of the image based on the degree of degradation and the degradation factors.

[0153] (Appendix 14) The recording medium described in Appendix 14 is a recording medium having recorded thereon a computer program that causes at least one computer to execute an information processing method that calculates the degree of quality degradation in an image, classifies the degradation factors that are the factors that caused the quality degradation of the image, and calculates a quality score that indicates the quality of the image based on the degree of degradation and the degradation factors.

[0154] (Appendix 15) The information processing system described in Appendix 15 is an information processing system including a degradation degree calculation means for calculating the degree of quality degradation in an image, a degradation factor classification means for classifying degradation factors that are factors that cause the quality of the image to deteriorate, and a quality score calculation means for calculating a quality score that indicates the quality of the image based on the degradation degree and the degradation factors.

[0155] (Appendix 16) The computer program described in Appendix 16 is a computer program that causes at least one computer to execute an information processing method that calculates a degree of quality degradation in an image, classifies degradation factors that are factors that have caused the quality degradation of the image, and calculates a quality score that indicates the quality of the image based on the degree of degradation and the degradation factors.

[0156] This disclosure may be modified as appropriate within the scope that does not contradict the gist or idea of ​​the invention that can be read from the claims and the entire specification, and information processing devices, information processing methods, and recording media that involve such modifications are also included in the technical idea of ​​this disclosure. [Explanation of symbols]

[0157] 10. Information processing equipment 11 processors 14 Storage device 16 Output Devices 110 Deterioration degree calculation unit 120 Deterioration factor classification section 130 Quality score calculation unit 140 Weight setting section 150 Deterioration degree determination unit 160 Authentication Section 170 Image Registration Unit 210 Loss function calculation unit 220 Gradient Calculation Unit 230 Parameter Update Unit

Claims

1. a degradation degree calculation means for calculating a degradation degree of quality in an image; a degradation factor classification means for classifying degradation factors that cause degradation of the image quality; a quality score calculation means for calculating a quality score indicating the quality of the image based on the degree of deterioration and the deterioration factor; an authentication means for performing an authentication process for an object included in the image using the image and the quality score, and outputting the degradation factor together with the result of the authentication process; Equipped with the authentication means calculates the degree of influence on the authentication process for each of the deterioration factors, and outputs the deterioration factor according to the degree of influence. Information processing device.

2. a weight setting unit for setting a weight corresponding to at least one of the deterioration degree and the deterioration factor; the quality score calculation means calculates the quality score based on the degree of deterioration, the deterioration factor, and the weight; The information processing device according to claim 1 .

3. the weight setting means sets the weight based on information regarding an output destination to which at least one of the image and the quality score is output. The information processing device according to claim 2 .

4. the weight setting means changes the weight in accordance with an environment when the image is captured.

4. The information processing device according to claim 2 or 3.

5. the deterioration degree calculation means calculates a plurality of deterioration degrees using a plurality of indexes different from each other; The information processing device according to claim 1 .

6. a deterioration degree determining means for determining whether the deterioration degree is higher than a predetermined threshold value; the deterioration factor classification means classifies the deterioration factor when it is determined that the degree of deterioration is higher than the predetermined threshold value; The information processing device according to claim 1 .

7. the authentication means determines whether the authentication process can be executed based on the quality score, and executes the authentication process if it is determined that the authentication process can be executed. The information processing device according to claim 1 .

8. the authentication means calculates a matching score from the image and outputs a result of the authentication process based on the matching score and the quality score. The information processing device according to claim 1 or 7.

9. further comprising an image registration means for registering a registration image to be used in the authentication process; The image registration means determines whether or not the registration image can be registered based on the quality score.

9. The information processing device according to claim 1, 7, or 8.

10. by at least one computer, Calculate the degree of quality degradation in the image, Classifying factors that cause deterioration in the quality of the image; calculating a quality score indicating the quality of the image based on the degree of degradation and the degradation factor; using the image and the quality score, performing an authentication process on an object included in the image, and outputting the degradation factor together with the result of the authentication process; When outputting the deterioration factors, a degree of influence on the authentication process is calculated for each of the deterioration factors, and the deterioration factors are output according to the degree of influence. Information processing methods.

11. At least one computer Calculate the degree of quality degradation in the image, Classifying factors that cause deterioration in the quality of the image; calculating a quality score indicating the quality of the image based on the degree of degradation and the degradation factor; using the image and the quality score, performing an authentication process on an object included in the image, and outputting the degradation factor together with the result of the authentication process; When outputting the deterioration factors, a degree of influence on the authentication process is calculated for each of the deterioration factors, and the deterioration factors are output according to the degree of influence. A computer program that executes an information processing method.

Images