Information processing system, information processing device, information processing method, and recording medium

Abstract

This information processing system is provided with an acquisition unit, a calculation unit, and a first output unit. The acquisition unit acquires an iris image including an iris. The calculation unit uses the acquired iris image to calculate, with regard to each of a plurality of degradation factors indicating a factor that causes the quality of the iris image to degrade, a factor score indicating a degree of quality corresponding to the relevant degradation factor. The first output unit outputs first output information in which the plurality of degradation factors and the factor scores corresponding respectively to the plurality of degradation factors are associated.

Description

Information processing system, information processing device, information processing method, and recording medium

[0001] The present disclosure relates to an information processing system, an information processing device, an information processing method, and a recording medium.

[0002] Various technologies related to iris authentication using iris images containing the iris have been proposed. For example, Patent Literature 1 discloses an information processing device including a display unit, an authentication image acquisition unit, and a display control unit. The authentication image acquisition unit described in Patent Literature 1 includes an iris camera for acquiring an authentication image containing the iris of a user's eye. When acquiring the authentication image, the display control unit described in Patent Literature 1 displays an authentication UI including a display for informing the user of the position of the iris camera on the display unit at a position corresponding to the position of the iris camera.

[0003] Patent Document 1 describes that an authentication image acquisition unit extracts an authentication image including an iris from an image captured by an iris camera. It also describes that if the authentication image acquisition unit is unable to extract an appropriate authentication image (e.g., appropriate size, brightness, clarity, etc.), it notifies the display control unit 12 of the reason. It also describes that the display control unit changes the guidance display of the authentication UI in accordance with the reason to extract an appropriate authentication image. Regarding this change in guidance display, Patent Document 1 describes that "if the eyes in the captured image are too small, the guidance display is changed to 'Too far away, please move closer to the iris camera.'"

[0004] Japanese Patent Application Laid-Open No. 2017-138846

[0005] The present disclosure aims to improve upon the techniques described in the prior art documents mentioned above.

[0006] The information processing system of the present disclosure includes an acquisition means for acquiring an iris image including an iris; a calculation means for calculating, using the acquired iris image, a factor score indicating the degree of quality corresponding to each of a plurality of degradation factors indicating factors that degrade the quality of the iris image; and a first output means for outputting first output information that associates the plurality of degradation factors with the factor scores corresponding to each of the plurality of degradation factors.

[0007] The information processing device of the present disclosure includes: an acquisition means for acquiring an iris image including an iris; a calculation means for calculating, using the acquired iris image, a factor score indicating the degree of quality corresponding to each of a plurality of degradation factors indicating factors that degrade the quality of the iris image; and a first output means for outputting first output information that associates the plurality of degradation factors with the factor scores corresponding to each of the plurality of degradation factors.

[0008] The information processing method of the present disclosure includes one or more computers acquiring an iris image including an iris, using the acquired iris image to calculate a factor score indicating the degree of quality corresponding to each of a plurality of degradation factors that indicate factors that degrade the quality of the iris image, and outputting first output information that associates the plurality of degradation factors with the factor score corresponding to each of the plurality of degradation factors.

[0009] The recording medium in the present disclosure is a recording medium having recorded thereon a program for causing one or more computers to execute the following operations: acquire an iris image including an iris; use the acquired iris image to calculate, for each of a plurality of degradation factors that indicate factors that degrade the quality of the iris image, a factor score that indicates the degree of quality corresponding to the degradation factor; and output first output information that associates the plurality of degradation factors with the factor score corresponding to each of the plurality of degradation factors.

[0010] 10 is a diagram illustrating an example configuration of a first information processing system according to the present disclosure. FIG. 11 is a block diagram illustrating an example configuration of a first information processing device according to the present disclosure. FIG. 12 is a flowchart illustrating an example processing operation of the first information processing device according to the present disclosure. FIG. 13 is a diagram illustrating an example of a first output unit according to the present disclosure. FIG. 14 is a diagram illustrating a first example of a first display screen. FIG. 15 is a diagram illustrating a second example of a first display screen. FIG. 16 is a diagram illustrating a third example of a first display screen. FIG. 17 is a diagram illustrating a fourth example of a first display screen. FIG. 18 is a diagram illustrating a fifth example of a first display screen. FIG. 19 is a diagram illustrating a sixth example of a first display screen. FIG. 20 is a diagram illustrating a seventh example of a first display screen. FIG. 21 is a diagram illustrating an example physical configuration of a first information processing device according to the present disclosure. FIG. 22 is a diagram illustrating an example configuration of a second information processing system and a second information processing device according to the present disclosure. FIG. 23 is a flowchart illustrating an example processing operation of the second information processing system and the second information processing device according to the present disclosure. FIG. 24 is a diagram illustrating an eighth example of a first display screen. FIG. 25 is a diagram illustrating an example configuration of a third information processing system and a third information processing device according to the present disclosure. FIG. 26 is a flowchart illustrating an example processing operation of the third information processing system and the third information processing device according to the present disclosure. FIG. 27 is a diagram illustrating another example of a first output unit according to the present disclosure. FIG. 28 is a diagram illustrating an example configuration of a fourth information processing system and a fourth information processing device according to the present disclosure. Fig. 1 is a diagram illustrating yet another example of a first output unit according to the present disclosure. Fig. 2 is a diagram illustrating configuration examples of a fifth information processing system and a fifth information processing device according to the present disclosure. Fig. 3 is a flowchart illustrating processing operation examples of the fifth information processing system and the fifth information processing device according to the present disclosure. Fig. 4 is a diagram illustrating configuration examples of a sixth information processing system and a sixth information processing device according to the present disclosure. Fig. 5 is a flowchart illustrating processing operation examples of the sixth information processing system and the sixth information processing device according to the present disclosure.

[0011] Hereinafter, embodiments of the present disclosure will be described with reference to the drawings. In all drawings, similar components are denoted by similar reference numerals, and descriptions thereof will be omitted as appropriate. In the present disclosure, the drawings relate to one or more embodiments.

[0012] [First Embodiment] (Overview) Generally, iris images are degraded due to various factors, which may reduce the accuracy of iris authentication using the iris images. The accuracy of iris authentication here may be expressed by at least one of, for example, an authentication score, an error rate, etc. Examples of the error rate include a false acceptance rate, a true rejection rate, an equal error rate (ERR), an are-under-the-curve (AUC) score, etc.

[0013] The false acceptance rate may be, for example, FAR (False Acceptance Rate), FPIR (False Positive Identification Rate), etc. The false rejection rate may be FRR (False Reject Rate), FNIR (False Negative Identification Rate), etc.

[0014] The quality of an iris image, which affects the accuracy of iris authentication, can be degraded by various factors, such as contrast, sharpness, effective iris area ratio, iris diameter pixel count, pupil dilation, grayscale gradation, pupil circularity, margin from the image edge, iris ellipticity, degree of focus blur, degree of motion blur, occlusion by eyeglasses, wearing eyeglasses, whether hard contact lenses are worn, whether colored contact lenses are worn, occlusion rate by hair or eyelashes, and degree of eye opening or closing.

[0015] According to the technology described in Patent Document 1, if the eyes in a captured image are too small, guidance can be provided to increase the size of the eyes in the image, potentially making it possible to capture an image of a larger eye.

[0016] However, in general, the quality of an iris image may be degraded due to multiple degradation factors. To improve the quality of an iris image whose quality is degraded due to multiple degradation factors, it is necessary to comprehensively understand and address these multiple degradation factors. With the technology described in Patent Document 1, it is difficult to comprehensively understand and address the multiple degradation factors. Therefore, with the technology described in Patent Document 1, it may be difficult to obtain a high-quality iris image that improves the accuracy of iris authentication.

[0017] One of the problems with the present disclosure is that it is difficult to obtain high-quality iris images that improve the accuracy of iris authentication.

[0018] (Configuration Example of Information Processing System S1) As shown in FIG. 1 , the information processing system S1 includes an acquisition unit 110, a calculation unit 120, and a first output unit 130.

[0019] The acquisition unit 110 acquires an iris image including an iris.

[0020] The calculation unit 120 uses the acquired iris image to calculate a factor score indicating the degree of quality corresponding to each of a plurality of degradation factors that indicate factors that degrade the quality of the iris image.

[0021] The first output unit 130 outputs first output information that associates a plurality of deterioration factors with factor scores corresponding to each of the plurality of deterioration factors.

[0022] According to this information processing system S1, by referring to the first output information, the user can infer, from among a plurality of degradation factors, which degradation factor needs to be addressed in order to acquire a high-quality iris image that improves the accuracy of iris authentication. Therefore, it becomes possible to more easily acquire a high-quality iris image that improves the accuracy of iris authentication.

[0023] (Configuration Example of Information Processing Device 100) As shown in FIG. 2, the information processing device 100 includes an acquisition unit 110, a calculation unit 120, and a first output unit 130.

[0024] The acquisition unit 110 acquires an iris image including an iris.

[0025] The calculation unit 120 uses the acquired iris image to calculate a factor score indicating the degree of quality corresponding to each of a plurality of degradation factors that indicate factors that degrade the quality of the iris image.

[0026] The first output unit 130 outputs first output information that associates a plurality of deterioration factors with factor scores corresponding to each of the plurality of deterioration factors.

[0027] According to the information processing device 100, by referring to the first output information, the user can infer, from among a plurality of degradation factors, which degradation factor needs to be addressed in order to acquire a high-quality iris image that improves the accuracy of iris authentication. Therefore, it becomes possible to more easily acquire a high-quality iris image that improves the accuracy of iris authentication.

[0028] (Example of Processing Operation of Information Processing Device 100) The information processing device 100 executes information processing as shown in FIG.

[0029] The acquisition unit 110 acquires an iris image including the iris (step S110).

[0030] Using the acquired iris image, the calculation unit 120 calculates a factor score indicating the degree of quality corresponding to each of a plurality of degradation factors that indicate factors that degrade the quality of the iris image (step S120).

[0031] The first output unit 130 outputs first output information that associates a plurality of deterioration factors with factor scores corresponding to each of the plurality of deterioration factors (Step S130).

[0032] According to this information processing, by referring to the first output information, the user can infer, from among multiple degradation factors, which degradation factor needs to be addressed in order to acquire a high-quality iris image that improves the accuracy of iris authentication, thereby making it easier to acquire a high-quality iris image that improves the accuracy of iris authentication.

[0033] Below, detailed examples of the information processing device 100 etc. will be described. Note that the information processing system S1 may be configured with a plurality of information processing devices that share all or part of the functions of the information processing device 100. This may also be the case in other embodiments.

[0034] (Regarding the Acquisition Unit 110) The acquisition unit 110 acquires, for example, one or more iris images including an iris.

[0035] In detail, for example, the acquisition unit 110 acquires a target image from at least one of a photographing device, an image storage unit, etc. (not shown). The target image is an image showing a target. The target is typically a person. Note that the target may also be an animal (e.g., a snake, a dog, etc.).

[0036] The image capturing device is, for example, a camera that captures an image of a target and generates an image of the target. The image capturing device may generate a moving image (video) or a still image. When the image capturing device generates a video, the acquisition unit 110 may acquire sequentially captured images of the target.

[0037] The image storage unit is, for example, a storage unit that stores one or more target images in advance.

[0038] The target image may be any image that shows a target. The target image may be, for example, one or more of a whole-body image, an upper-body image, a face image, a binocular image, a monocular image, an iris image, etc. A whole-body image is an image that includes the whole body of the target. A upper-body image is an image that includes the upper half of the target's body. A face image is an image that includes the target's face. A binocular image is an image that includes both of the target's eyes. A monocular image is an image that includes either the left or right eye of the target. An iris image is an image that includes either the left or right iris of the target.

[0039] The iris image may include, for example, the iris as described above. That is, as long as the iris of the subject is captured, the iris image may be a whole-body image, an upper-body image, a face image, a binocular image, a monocular image, or the like.

[0040] Furthermore, for example, the acquisition unit 110 may perform image processing on the acquired target image to acquire an iris image including the iris of the target. The image processing may include, for example, at least one process of detecting a predetermined region (iris region) including the iris in the target image and cutting out the iris region from the target image. The image processing may include, for example, a process of transforming the cut-out iris region into a predetermined shape. Note that when the acquisition unit 110 performs image processing to acquire an iris image, this image processing is not limited to the example exemplified here.

[0041] Furthermore, for example, the acquisition unit 110 may acquire multiple target images captured at the same time. In this case, the acquisition unit 110 may acquire an iris image by performing image processing on one or more of the acquired target images. This image processing may include, for example, at least one of a process of detecting a predetermined area (iris area) containing an iris in the target image, a process of cutting out the iris area from the target image, and a process of transforming the cut-out iris area into a predetermined shape. Note that the "same time" may be substantially the same time, for example, within a predetermined length of time.

[0042] (Regarding the calculation unit 120) The calculation unit 120 calculates a factor score for each of a plurality of predetermined deterioration factors, for example, by using the iris image acquired by the acquisition unit 110. That is, the calculation unit 120 calculates a plurality of factor scores. The plurality of predetermined deterioration factors and the plurality of factor scores may be associated with each other. In detail, for example, the plurality of predetermined deterioration factors and the plurality of factor scores may be associated with each other on a one-to-one basis.

[0043] Each of the multiple degradation factors is information indicating a factor that degrades the quality of the iris image. The factor score is a score indicating the level of quality corresponding to the degradation factor. This score may be, for example, a numerical value. Note that the factor score calculated by the calculation unit 120 may be expressed using letters, symbols, etc. other than numerical values.

[0044] The calculation unit 120 may use, for example, a trained calculation model to calculate the factor scores by inputting an iris image. The calculation model is, for example, a machine learning model configured using a neural network. The calculation model may be trained using an iris image for training and ground truth data including a plurality of degradation factors related to the iris image and their respective factor scores. Note that the method by which the calculation unit 120 calculates the factor scores is not limited to the method using a machine learning model.

[0045] (Regarding Degradation Factors) The multiple degradation factors may be selected in advance from, for example, contrast, sharpness, effective iris area ratio, iris diameter pixel count, pupil dilation rate, grayscale gradation, pupil circularity, margin from image edge, iris ellipticity, degree of focus blur, degree of motion blur, occlusion due to eyeglass reflection, wearing eyeglasses, whether hard contact lenses are worn, whether colored contact lenses are worn, rate of occlusion by hair or eyelashes, degree of eye opening or closing, vertical off-angle, horizontal off-angle, etc. Note that the degradation factors for which calculation unit 120 calculates the factor score are not limited to those exemplified here.

[0046] (First Output Unit 130) The first output unit 130 outputs first output information that associates a plurality of deterioration factors with factor scores corresponding to each of the plurality of deterioration factors.

[0047] As shown in FIG. 4 , the first output unit 130 includes, for example, a deviation calculation unit 131 , a first output control unit 132 , a first display unit 133 , and a first speaker 134 .

[0048] The deviation calculation unit 131 calculates a deviation indicating the degree of difference between the factor score calculated by the calculation unit 120 and a predetermined threshold value for each of the plurality of deterioration factors.

[0049] The predetermined threshold may be determined for each degradation factor, for example. In more detail, for example, iris images with different factor scores for a degradation factor may be created by image processing, and the threshold may be determined based on the factor score that results in a desired accuracy of iris authentication. This threshold may be, for example, an end value of the range of factor scores that results in a desired accuracy of iris authentication.

[0050] The threshold value may be a common value for some or all of the multiple degradation factors.

[0051] The deviation may be normalized using a threshold value so that the value falls within a range of 0 to 1. In particular, the deviation may be calculated by dividing the difference from the factor score threshold value by the threshold value.

[0052] The first output control unit 132 generates first output information that associates a plurality of deterioration factors with factor scores corresponding to each of the plurality of deterioration factors. The first output control unit 132 generates the first output information, for example, by using the factor scores calculated for each of the plurality of deterioration factors by the calculation unit 120. Furthermore, for example, the first output control unit 132 may generate the first output information by further using the deviations calculated for each of the plurality of deterioration factors by the deviation calculation unit 131.

[0053] The first output information includes, for example, a first display screen and a first sound.

[0054] (Regarding the first display screen) The first display screen includes a score display area that associates a plurality of deterioration factors with factor scores corresponding to each of the plurality of deterioration factors for at least one of the left and right eyes. The first display screen may also include an image display area that includes at least one target image related to the score display area.

[0055] The target image related to the score display area may include, for example, an iris image that was used to calculate the factor score associated in the score display area, a target image that was used to create the iris image, etc. The related image may include a target image that was taken at the same time as the iris image or the target image, etc.

[0056] (Score Display Area) The score display area is an area that displays, for example, an image in which a plurality of deterioration factors are associated with factor scores corresponding to each of the plurality of deterioration factors.

[0057] Each of the multiple deterioration factors may be displayed in the score display area by, for example, characters indicating a title such as a predetermined name. Note that the predetermined title of the deterioration factor may be displayed in the score display area using an illustration, a symbol, or the like, or may be displayed using other methods.

[0058] (Example of a method for displaying a factor score corresponding to one iris image) The factor score may be displayed in the score display area using, for example, a score display diagram of a predetermined shape. That is, the score display area includes, for example, a score display diagram that represents the magnitude of the corresponding factor score for each of a plurality of deterioration factors by the size of the area of ​​a figure of a predetermined shape.

[0059] In detail, for example, the factor scores may be represented by a bar graph, a pie chart, the size of the corresponding title, etc. (see, for example, FIGS. 5 to 10).

[0060] In the case of a bar graph, the score display diagram is, for example, a strip-shaped (e.g., rectangular) figure of a predetermined width. The size of the factor score is represented, for example, by the length of the score display diagram. When the width of the bar graphs representing each factor score is the same, it can also be said that the size of the factor score is represented by the size of the strip-shaped figure.

[0061] In the case of a pie chart, the score display diagram is, for example, a concentric sector-shaped figure. The magnitude of the factor score may be represented, for example, by the central angle of the sector or by the radius of the sector. In either case, the magnitude of the factor score can also be said to be represented by the area of ​​the sector.

[0062] The score display diagram may include a line indicating a predetermined threshold value for each of a plurality of deterioration factors. The position of the line indicating the threshold value in the score display diagram may be fixed or variable. The area of ​​a figure representing the magnitude of a corresponding factor score may correspond to a size relative to a predetermined reference value for the factor score. When the position of the line indicating the threshold value is fixed, the reference value may be a predetermined threshold value.

[0063] The plurality of deterioration factors may include at least one continuous deterioration factor and at least one discrete deterioration factor. The continuous deterioration factor is a deterioration factor whose factor score is expressed as a continuous value. The discrete deterioration factor is a deterioration factor whose factor score is expressed as a discrete value. The first display screen may display the corresponding factor scores using different display modes for the continuous deterioration factor and the discrete deterioration factor.

[0064] Some deterioration factors are, by their nature, represented by multiple discrete values. In the examples of deterioration factors described above, whether or not the wearer wears glasses, whether or not the wearer wears hard contact lenses, and whether or not the wearer wears colored contact lenses are, by their nature, deterioration factors represented by binary values. Such deterioration factors represented by binary values ​​may, by their nature, be included in discrete deterioration factors. Furthermore, for example, wearing glasses may be represented by three or more discrete values, such as not wearing glasses, wearing glasses with colored lenses (so-called sunglasses), wearing glasses with non-colored lenses, etc. Wearing glasses is an example of a deterioration factor that, by its nature, is represented by three or more discrete values.

[0065] Furthermore, in the examples of the degradation factors described above, other degradation factors can be expressed by continuous values ​​in nature. Whether such degradation factors are continuous degradation factors or discrete degradation factors may be determined in advance. The continuous values ​​can be expressed by discrete values, for example, using values ​​associated with two or more predetermined ranges. Therefore, degradation factors that can be expressed by continuous values ​​in nature may be treated as discrete degradation factors.

[0066] The different display modes may be different types of display modes such as figures, letters, numbers, symbols, codes, illustrations, etc., or may be display modes of the same type that have different colors, line types, sizes, font types, backgrounds, etc.

[0067] 5 is a diagram showing a first example of the first display screen, which includes a score display area P1 and an image display area Q1.

[0068] The score display area P1 includes a bar graph showing five or more deterioration factors and the factor scores of each of the deterioration factors. In the bar graph, the magnitude of the factor score is represented by the length of a rectangle of the same width.

[0069] The associated deterioration factors and bar graphs may be displayed in a predetermined order, or may be displayed in descending order of the degree of deviation. By displaying the deterioration factors in descending order of the degree of deviation, it is possible to make it easier for the user to recognize deterioration factors with large degrees of deviation.

[0070] Furthermore, multiple lines B are included at fixed positions common to five or more degradation factors. The multiple lines B indicate thresholds for the corresponding degradation factors. The calculated factor scores may be normalized so that the thresholds are located on the lines B. The length of the rectangle may be, for example, a length corresponding to the normalized values.

[0071] By including an image showing a threshold such as line B, it is possible to easily recognize whether the factor score of the degradation factor exceeds the threshold.

[0072] The method of recognizably displaying the threshold is not limited to an image showing the threshold, such as line B. For example, depending on whether the factor score exceeds the threshold, a graphic (i.e., a graph) showing the factor score, a title showing the deterioration factor corresponding to the factor score, or the like may be displayed in different display modes. For example, the graphic, title, or the like may be displayed in blue if the threshold is exceeded, and in red if the threshold is not exceeded.

[0073] Furthermore, for example, when the factor score does not exceed the threshold, the display mode of the graphic, title, etc. may continuously change according to the magnitude of the factor score. In detail, for example, the color of the graphic, title, etc. may continuously change from red to blue as the factor score approaches the threshold, and may be displayed in blue when the factor score is equal to or greater than the threshold.

[0074] Furthermore, for degradation factors that have an optimum range (existing between a threshold and another threshold), such as brightness, contrast, pupil dilation, etc., two thresholds may be set. Depending on whether the factor is within the range, the graphic (i.e., graph) representing the factor score, the title indicating the degradation factor, etc. may be displayed in different ways.

[0075] When the factor score of a discrete degradation factor, such as whether or not hard contact lenses are worn, is represented using a bar graph, a title corresponding to the discrete degradation factor may be displayed only when the iris image quality is not in a predetermined desired state. For example, the words "wearing colored contact lenses" may be displayed only when hard contact lenses are worn. Also, for example, the factor score of a discrete degradation factor may be displayed in a different display mode depending on the factor score.

[0076] For a discrete deterioration factor whose factor score is expressed by three or more discrete values, the factor score may be expressed by discrete values ​​corresponding to a threshold value vicinity, which is a predetermined range based on the threshold value, a value greater than the threshold value vicinity, and a value smaller than the threshold value vicinity. A graphic (i.e., a graph) representing the factor score, a title indicating the deterioration factor, etc. may be displayed in different ways depending on the value of the factor score.

[0077] That is, the score display diagram may display the factor score in a different display mode depending on whether the factor score is within a predetermined range with respect to a predetermined threshold value.

[0078] The image display area Q1 includes three target images (i.e., a target upper body image, a left eye image, and a right eye image) associated with the score display area P1.

[0079] 6 is a diagram showing a second example of the first display screen, which includes two score display areas P2 and an image display area Q2.

[0080] The two score display areas P2 include a score display area P2 for the right eye and a score display area P2 for the left eye. Each of the score display areas P2, like the score display area P1, includes five or more deterioration factors and a bar graph representing the factor score for each of the deterioration factors. Like the score display area P1, this bar graph also includes a line B indicating a threshold value.

[0081] The image display area Q2 is included between the two score display areas P2 and includes three target images (i.e., a target upper body image, a left eye image, and a right eye image) associated with the two score display areas P2.

[0082] (Regarding a third example of the first display screen) Fig. 7 is a diagram showing a third example of the first display screen. The figure shows an example of a first display screen including two score display areas P3 and an image display area Q3. In the first display screen shown in the figure, score display areas P3 for the right eye and left eye are arranged adjacent to each other to the right of the image display area Q3. Except for this point, the configuration of the first display screen shown in Fig. 7 is the same as the configuration of the first display screen shown in Fig. 6.

[0083] By arranging the score display area P3 for the right eye and the score display area P3 for the left eye side by side, the amount of line of sight that the user has to move in order to refer to the factor scores corresponding to each of the left and right eyes can be reduced, making it easier to compare the factor scores corresponding to each of the left and right eyes.

[0084] (Regarding the fourth example of the first display screen) Fig. 8 is a diagram showing a fourth example of the first display screen. The figure shows an example of the first display screen including a score display area P4. The score display area P4 includes a plurality of deterioration factors and a pie chart showing the magnitude of the factor score for each of the deterioration factors. In the pie chart shown in the figure, the magnitude of the factor score for each of the plurality of deterioration factors is represented by the size of the central angle of a concentric sector.

[0085] Furthermore, the sectors corresponding to the multiple degradation factors are arranged so as not to overlap each other, so that when the total factor score of the multiple degradation factors increases, the sectors as a whole become larger and rotate clockwise, as indicated by the dotted arrow in Figure 8.

[0086] In such a case, the maximum area of ​​the graphic (a sector in the example of FIG. 8 ) corresponding to the factor score may be determined according to the number of multiple degradation factors. For example, the maximum area of ​​the graphic may be a value that is a predetermined value greater than 360 degrees divided by the number of degradation factors. In more detail, for example, if the number of degradation factors is four as shown in FIG. 8 and the predetermined value is 10 degrees, the maximum area may be 100 (= 360 / 4 + 10) degrees. For example, if the number of degradation factors is six and the predetermined value is 10 degrees, the maximum area may be 70 (= 360 / 6 + 10) degrees. Note that the predetermined value is not limited to 10 degrees and may be determined as appropriate.

[0087] This allows the user to easily visually see how much the factor score for each degradation factor falls short of the maximum value, allowing the user to easily estimate how much improvement is needed for each degradation factor.

[0088] (Regarding the fifth example of the first display screen) FIG. 9 is a diagram showing a fifth example of the first display screen. The figure shows an example of the first display screen including a score display area P5. The score display area P5 includes a plurality of deterioration factors and a pie chart showing the magnitude of the factor score for each of the deterioration factors. In the pie chart shown in the figure, the magnitude of the factor score for each of the plurality of deterioration factors is represented by the length of the radius of a concentric sector. The central angles of the plurality of sectors representing each of the plurality of deterioration factors are equal to each other.

[0089] The score display area P5 includes a dotted circle C concentric with the sector. This circle C indicates thresholds corresponding to multiple degradation factors. In other words, circle C is included in a fixed position common to multiple degradation factors. The calculated factor scores may be normalized so that the thresholds are located on circle C. The radius of the sector may be, for example, a length corresponding to the normalized value.

[0090] 10 is a diagram showing a sixth example of the first display screen. The figure shows an example of the first display screen including a score display area P6. In the score display area P5, titles indicating each of a plurality of deterioration factors are displayed in sizes corresponding to the magnitude of the factor score, deviation, etc.

[0091] Furthermore, the display position of the corresponding title may be changed depending on the magnitude of the factor score, deviation, etc. For example, the title may be positioned closer to the center of the first display screen as the corresponding factor score, deviation, etc. is larger.

[0092] The title may be displayed in a different display mode depending on whether the factor score is equal to or greater than a threshold. For example, the title may be displayed in a predetermined display mode (e.g., in an inconspicuous display object) when the factor score is equal to or greater than the threshold. In this case, when the factor score is smaller than the threshold, the title may be displayed in a conspicuous display mode that differs from the predetermined display mode. An inconspicuous display mode may be, for example, a smaller display size than in the conspicuous display mode, or a lighter color than in the conspicuous display mode. The inconspicuous display mode is not limited to the examples given here.

[0093] (Example of a method for displaying factor scores corresponding to multiple iris images) For example, the score display area may display an image in which multiple deterioration factors are associated with a diagram showing changes over time in the factor scores corresponding to each of the multiple deterioration factors. Such a score display area is suitable, for example, when the acquisition unit 110 acquires video. In this case, the acquisition unit 110 may continuously acquire multiple iris images. Then, the calculation unit 120 may calculate a factor score for each of the multiple iris images continuously acquired. In this case, the calculation unit 120 may, for example, sequentially calculate the factor score for the multiple iris images continuously acquired.

[0094] 11 is a diagram showing a seventh example of the first display screen. The figure shows an example of the first display screen including a score display area P6. The score display area P6 includes titles of the four deterioration factors and a line graph showing the factor scores at times T1 to T4.

[0095] The time interval between times T1 and T4 may be determined as appropriate, for example, as a time interval that allows the user to view the score display area P6 and take action to improve the factor score in the next capture. Furthermore, for example, the time interval between times T1 and T4 may be an update time interval for the display that displays the score display area P6. If multiple factor scores are calculated at each time interval, the factor score displayed in the score display area P6 may be an average value of the multiple factor scores.

[0096] The method of representing the factor scores is not limited to graphics. For example, the factor scores may be represented by the scores themselves, by using predetermined characters, illustrations, predetermined symbols, or the like according to the scores, or by other methods.

[0097] (Regarding the first voice) The first voice is a voice that conveys a plurality of degradation factors and factor scores corresponding to each of the plurality of degradation factors in association with each other. The first voice is a voice that conveys, for example, for the plurality of degradation factors in order, the title of the degradation factor, and at least one of the factor score of the degradation factor, whether or not the factor score exceeds a threshold, the degree of deviation, etc.

[0098] (First display unit 133) The first display unit 133 displays the first display screen included in the first output information under the control of the first output control unit 132. That is, outputting the first output information includes displaying the first display screen as the first output information.

[0099] (First Speaker 134) The first speaker 134 outputs the first sound included in the first output information under the control of the first output control unit 132. That is, outputting the first output information includes outputting (emitting) the first sound as the first output information.

[0100] The first output unit 130 may include only one of the first display unit 133 and the first speaker 134. In this case, the first output information may include only information of the first display screen and the first audio corresponding to either the first display unit 133 or the first speaker 134. The first output control unit 132 may control either the first display unit 133 or the first speaker 134.

[0101] (Example of physical configuration of information processing device 100) The information processing device 100 physically includes a bus 1010, a processor 1020, a memory 1030, a storage device 1040, a network interface 1050, an input interface 1060, and an output interface 1070, as shown in FIG.

[0102] The bus 1010 is a data transmission path for transmitting and receiving data among the processor 1020, memory 1030, storage device 1040, network interface 1050, input interface 1060, and output interface 1070. However, the method of connecting the processor 1020 and the like to each other is not limited to bus connection.

[0103] The processor 1020 is implemented by a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), or the like.

[0104] The memory 1030 is a main storage device realized by a RAM (Random Access Memory) or the like.

[0105] 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 the functions of the information processing device 100. The processor 1020 reads each of these program modules into the memory 1030 and executes them to realize the function corresponding to the program module.

[0106] The network interface 1050 is an interface for connecting the information processing device 100 to a network. The network is a communication network for transmitting and receiving information to and from other devices (not shown), and may be wired, wireless, or a combination of these.

[0107] The input interface 1060 is an interface for the user to input information, and is composed of, for example, a touch panel, a keyboard, a mouse, and the like.

[0108] The output interface 1070 is an interface for presenting information to the user, and is configured, for example, by a liquid crystal panel, an organic EL (Electro-Luminescence) panel, etc. The output interface 1070 may also include a speaker.

[0109] Although the information processing system S1 and the information processing device 100 are physically configured from one device (e.g., a computer), the information processing device 100 may be configured from multiple devices (e.g., computers) that transmit and receive information to and from each other via a network NT. In this case, the multiple devices may cooperate to execute information processing.

[0110] As described above, according to this embodiment, the information processing system S1 includes the acquisition unit 110, the calculation unit 120, and the first output unit 130. The acquisition unit 110 acquires an iris image including an iris. The calculation unit 120 uses the acquired iris image to calculate, for each of a plurality of degradation factors that indicate factors that degrade the quality of the iris image, a factor score that indicates the level of quality corresponding to the degradation factor. The first output unit 130 outputs first output information that associates the plurality of degradation factors with the factor scores corresponding to each of the plurality of degradation factors.

[0111] This allows the user to refer to the first output information and guess from among multiple degradation factors which degradation factor is affecting the quality degradation of the iris image, i.e., which degradation factor needs to be addressed in order to acquire a high-quality iris image that will improve the accuracy of iris authentication. Therefore, it becomes possible to more easily acquire a high-quality iris image that will improve the accuracy of iris authentication.

[0112] Furthermore, because the factor scores are output, the user can estimate the degree to which action is required for each degradation factor. This makes it easier to obtain high-quality iris images that improve the accuracy of iris authentication.

[0113] Furthermore, it is possible to output a factor score for specific shooting conditions, including the shooting environment, shooting device, etc., used in shooting to obtain the iris image. Therefore, it is possible to infer from among multiple degradation factors the degradation factor that is affecting the quality degradation of the iris image under specific shooting conditions. Therefore, it is possible to take measures appropriate to the specific shooting conditions, making it possible to more easily obtain high-quality iris images.

[0114] For example, when the first output information is output in real time in response to the capture of an iris image, the user can immediately take necessary measures to obtain a high-quality iris image under the capture conditions and then capture another image. Furthermore, the user can also repeatedly capture images by referring to the first output information. Therefore, it becomes possible to more easily and reliably obtain a high-quality iris image.

[0115] According to this embodiment, outputting the first output information includes displaying the first display screen as the first output information, the first display screen including a score display area that associates a plurality of deterioration factors with factor scores corresponding to each of the plurality of deterioration factors for at least one of the left and right eyes.

[0116] This makes it possible to estimate, from among multiple degradation factors, the degradation factor that needs to be addressed in order to acquire high-quality iris images that improve the accuracy of iris authentication for each of the left and right eyes, making it easier to acquire high-quality iris images that improve the accuracy of iris authentication for each of the left and right eyes.

[0117] According to this embodiment, the score display area includes a score display diagram that represents the magnitude of the corresponding factor score for each of the plurality of deterioration factors by the size of the area of ​​a figure having a predetermined shape. The score display diagram includes a line indicating a predetermined threshold value for each of the plurality of deterioration factors.

[0118] This allows the user to easily understand the causes of degradation that need to be addressed in order to obtain a high-quality iris image, and the extent of the degradation, making it easier to obtain a high-quality iris image that improves the accuracy of iris authentication.

[0119] According to this embodiment, the maximum value of the area of ​​the graphic corresponding to the factor score is determined according to the number of multiple degradation factors.

[0120] This allows the user to easily understand the causes of degradation that need to be addressed in order to obtain a high-quality iris image, and the extent of the degradation, making it easier to obtain a high-quality iris image that improves the accuracy of iris authentication.

[0121] According to this embodiment, the position of the line indicating the threshold in the score display diagram is fixed or variable. The area of ​​the figure representing the magnitude of the corresponding factor score corresponds to the size relative to a predetermined reference value for the factor score. When the position of the line indicating the threshold is fixed, the reference value is a predetermined threshold.

[0122] This allows the user to easily understand the causes of degradation that need to be addressed in order to obtain a high-quality iris image, and the extent of the degradation, making it easier to obtain a high-quality iris image that improves the accuracy of iris authentication.

[0123] According to this embodiment, the score display diagram shows the factor score in a different display mode depending on whether the factor score is within a predetermined range with respect to a predetermined threshold value.

[0124] This allows the user to easily understand the causes of degradation that need to be addressed in order to obtain a high-quality iris image, and the extent of the degradation, making it easier to obtain a high-quality iris image that improves the accuracy of iris authentication.

[0125] According to this embodiment, the plurality of deterioration factors includes at least one continuous deterioration factor whose factor score is expressed as a continuous value and at least one discrete deterioration factor whose factor score is expressed as a discrete value. The score display area displays the corresponding factor scores using different display modes for the continuous deterioration factor and the discrete deterioration factor.

[0126] This allows the user to easily understand whether or not a measure is necessary to acquire a high-quality iris image for each of the continuous and discrete degradation factors, making it easier to acquire a high-quality iris image that improves the accuracy of iris authentication.

[0127] According to this embodiment, the score display area displays an image in which a plurality of deterioration factors are associated with a diagram showing the change over time in the factor score corresponding to each of the plurality of deterioration factors.

[0128] This allows the user to understand the results of measures taken to acquire high-quality iris images for the degradation factors, and easily understand whether or not further measures are necessary, making it easier to acquire high-quality iris images that improve the accuracy of iris authentication.

[0129] [Embodiment 2] In this embodiment, an example will be described in which the positions of predetermined key points (key point positions) are estimated from an iris image and then factor scores are calculated using the estimated positions. Note that, for the sake of brevity, descriptions that overlap with other embodiments will be omitted as appropriate.

[0130] (Configuration example of information processing system S2 and information processing device 200) As shown in FIG. 13, the information processing system S2 and the information processing device 200 include an acquisition unit 110 and a first output unit 130 similar to those in embodiment 1, an estimation unit 240, and a calculation unit 220.

[0131] The estimation unit 240 uses the iris image acquired by the acquisition unit 110 to estimate key point positions that indicate the positions of predetermined key points on the iris.

[0132] The calculation unit 220 calculates a factor score for each of the plurality of deterioration factors using the iris image acquired by the acquisition unit 110 and the key point positions estimated by the estimation unit 240 .

[0133] (Example of Processing Operation of Information Processing System S2 and Information Processing Device 200) The information processing system S2 and the information processing device 200 execute information processing as shown in FIG.

[0134] Step S110 is executed in the same manner as in the first embodiment.

[0135] The estimation unit 240 uses the iris image acquired in step S110 to estimate key point positions that indicate the positions of predetermined key points on the iris (step S240).

[0136] The calculation unit 220 calculates a factor score for each of the multiple deterioration factors using the iris image acquired in step S110 and the key point positions estimated in step S240 (step S220).

[0137] Step S130 is executed in the same manner as in the first embodiment.

[0138] (Regarding the Estimation Unit 240) As described above, the estimation unit 240 estimates key point positions using an iris image. The key point positions are information indicating the positions of predetermined key points on the iris.

[0139] The key points may include, for example, at least one of the center of the pupil circle, the radius or diameter of the pupil circle, the center of the iris circle, the radius or diameter of the iris circle, and a predetermined point on the eyelid (e.g., the upper end, lower end, left end, right end, center of the upper eyelid, center of the lower eyelid, etc.). Furthermore, if the shape of one or both of the pupil and the iris is estimated as an ellipse instead of a circle, the lengths of the major and minor axes may be estimated instead of the above-mentioned radius. The radius, diameter, length of the major axis, and length of the minor axis may be expressed in terms of the number of pixels.

[0140] The estimation unit 240 may estimate keypoint positions using an iris image as input, for example, by using a trained estimation model. The estimation model is, for example, a machine learning model configured using a neural network. The estimation model may be trained using a training iris image and correct answer data including keypoint positions related to the iris image. Note that the method by which the estimation unit 240 estimates keypoint positions is not limited to the method using a machine learning model.

[0141] (Calculation Unit 220) The calculation unit 220 differs from the calculation unit 120 according to the first embodiment in that the calculation unit 220 further uses the key point positions estimated by the estimation unit 240 to calculate the factor scores.

[0142] For example, the calculation unit 220 may extract the iris diameter from the key point positions. For example, the calculation unit 220 may calculate the pupil dilation rate from the ratio of the number of pixels in the diameter of the iris circle to the number of pixels in the diameter of the pupil circle. Note that the method for calculating the pupil dilation rate is not limited to this.

[0143] The calculation unit 220 may calculate the pupil circularity (or ellipticity) from the ratio of the lengths of the major and minor axes of the pupil ellipse, for example. The calculation unit 220 may identify the iris position closest to the edge of the image using the center and radius of the iris circle, for example, and calculate the number of pixels from the edge of the image (margin). The calculation unit 220 may calculate the degree of eye opening and closing using the position of the eyelid, for example.

[0144] Using the estimated keypoint positions, the calculation unit 220 can simultaneously calculate factor scores corresponding to multiple deterioration factors such as the pupil dilation rate, iris diameter, and eye open / close degree exemplified here. Therefore, the calculation unit 220 can calculate the factor scores at high speed with less processing load than when calculating using only the iris image.

[0145] The calculation unit 220 may, for example, use key point positions to cut out a rectangular area including the iris from the iris image. The calculation unit 220 may then calculate a factor score using, for example, the cut-out rectangular area. The degradation factor corresponding to the calculated factor score may be, for example, at least one of contrast, sharpness, grayscale gradation, degree of focus blur, degree of motion blur, whether or not the subject wears glasses, whether or not the subject wears hard contact lenses, whether or not the subject wears colored contact lenses, and the occlusion rate of hair or eyelashes. Note that the degradation factors corresponding to the factor score calculated by the calculation unit 220 from the cut-out rectangular area are not limited to these.

[0146] By extracting a rectangular region including the iris from the iris image in this way, the amount of processing can be reduced. Furthermore, the factor scores can be calculated using an image similar to the image from which the feature vectors used in iris authentication are extracted. This makes it possible to speed up the process for estimating the factor scores and improve the accuracy of the estimated factor scores.

[0147] The calculation unit 220 may calculate the factor scores by inputting an iris image using, for example, a trained calculation model. The calculation model is, for example, a machine learning model configured using a neural network. The calculation model may be trained using an iris image for training and ground truth data including key point positions related to the iris image, multiple degradation factors, and their respective factor scores. Note that the method by which the calculation unit 220 calculates the factor scores is not limited to the method using a machine learning model.

[0148] As described above, according to this embodiment, the information processing system S2 includes the estimation unit 240 and the calculation unit 220. The estimation unit 240 estimates key point positions indicating positions of predetermined key points on the iris, using the iris image acquired by the acquisition unit 110. The calculation unit 220 calculates a factor score for each of a plurality of deterioration factors, using the acquired iris image and the estimated key point positions.

[0149] This allows the factor scores to be calculated quickly, making it easier to obtain high-quality iris images that improve the accuracy of iris authentication.

[0150] Third Embodiment The image display areas Q1 to Q3 may include an iris guide, which is an image that indicates a predetermined position where the subject's iris should be displayed.

[0151] In this embodiment, the diagrams showing the configurations and processing operations of the information processing system and information processing device may be the same as those in embodiment 1. Therefore, this embodiment will also be described with reference to Figures 2 and 3. Note that descriptions that overlap with other embodiments will be omitted as appropriate for the sake of brevity.

[0152] The acquisition unit 110 may acquire a target image captured by an imaging device (not shown). The first display screen may include an image display area showing the target image. The image display area may include an iris guide for at least one of the left and right eyes, the iris guide indicating a predetermined position where the target's iris should be reflected.

[0153] 15 is a diagram showing an eighth example of the first display screen. This figure shows an example of the first display screen including an image display area Q4 and the score display area P1 shown in FIG. 5. The image display area Q4 is an example of an image display area including an iris guide G.

[0154] The image display area Q4 includes three target images (i.e., an upper body image, a left eye image, and a right eye image) related to the score display area P1. The image display area Q4 shows an example in which the target image showing the upper body of the target includes an iris guide G. The iris guide G included in the image display area Q4 indicates, with dotted frames, predetermined positions where the target's iris should be reflected for each of the left and right eyes.

[0155] The method for displaying the iris guide G is not limited to the example given here.

[0156] As described above, according to the present embodiment, in the information processing system S2, the acquisition unit 110 acquires a target image captured by an imaging device. The first display screen includes an image display area showing the target image. The image display area includes an iris guide that indicates a predetermined position where the iris of the target should be reflected for at least one of the left and right eyes.

[0157] This allows the subject to be guided so that the subject's iris is positioned at the position of the iris guide G, making it possible to capture a desirable iris image. Therefore, it becomes possible to more easily obtain a high-quality iris image that improves the accuracy of iris authentication.

[0158] [Embodiment 4] In this embodiment, an example will be described in which the first output information includes feedback information for improving the quality of an iris image. Note that, for the sake of brevity, descriptions that overlap with other embodiments will be omitted as appropriate.

[0159] (Configuration Example of Information Processing System S4 and Information Processing Device 400) As shown in FIG. 16, the information processing system S4 and the information processing device 400 include the same acquiring unit 110 and calculating unit 120 as in the first embodiment, and a first output unit 430.

[0160] The first output unit 430 outputs first output information. The first output information includes feedback information for improving the quality of the iris image. The feedback information is information generated based on a deviation indicating the degree of difference between the factor score calculated for each of the plurality of degradation factors and a predetermined threshold, and a feedback rule predetermined for the deviation.

[0161] (Example of Processing Operation of Information Processing System S4 and Information Processing Device 400) The information processing system S4 and the information processing device 400 execute information processing as shown in FIG.

[0162] Steps S110 and S120 are executed in the same manner as in the first embodiment.

[0163] The first output unit 430 outputs first output information (step S430). The first output information includes feedback information for improving the quality of the iris image. The feedback information is information generated based on a deviation indicating the degree of difference between the factor score calculated for each of the plurality of degradation factors and a predetermined threshold, and a feedback rule predetermined for the deviation.

[0164] (Regarding the First Output Unit 430) The first output unit 430 generates feedback information based on, for example, the degree of deviation and a predetermined feedback rule related to the degree of deviation. The degree of deviation is a value (score) indicating the degree of difference between the factor score calculated for each of the multiple degradation factors and a predetermined threshold. The first output unit 430 outputs, for example, first output information including the generated feedback information. The feedback information may be notified to the user by display and / or sound. The feedback information may be output to a device.

[0165] In this embodiment, the first output information may further include information similar to that in the first embodiment (i.e., information associating multiple deterioration factors with factor scores corresponding to each of the multiple deterioration factors).

[0166] As shown in FIG. 18, the first output unit 430 includes a deviation calculation unit 131 similar to that of embodiment 1, a first output control unit 432, a first display unit 433, a first speaker 434, and a first communication unit 435.

[0167] (First Output Control Unit 432) The first output control unit 432 generates feedback information based on, for example, the deviation calculated by the deviation calculation unit 131 and a feedback rule that is predetermined regarding the deviation.

[0168] In detail, for example, the feedback rule may include a predetermined message regarding a degradation factor indicating that the deviation degree has deteriorated more than a predetermined value, a degradation factor indicating that the deviation degree is outside a predetermined range, etc. This message may be a message that guides the subject to improve the quality of the iris image.

[0169] The feedback rule may include, for example, a message prompting the user to move closer to the image capture device (e.g., a camera) if the iris diameter pixel count is smaller than a predetermined value. The feedback rule may include, for example, a message prompting the user to widen the eyelids if the eye opening degree is smaller than a predetermined value. The feedback rule may include, for example, a message prompting the user to look directly at the image capture device if the pupil circularity is smaller than a predetermined value.

[0170] The feedback rule may include, for example, a message prompting the user to remove their glasses if their glasses are blocking their iris, or a message prompting the user to take an action to remove the blocking, such as brushing their hair back, if their hair or eyelashes are blocking their iris.

[0171] The feedback rule may include, for example, a message prompting the user to take an action to position the eye in a desired position when the iris is out of frame and not in a desired area, or a message prompting the user to take an action to position the eye in a desired focus position when the iris image is out of focus.

[0172] The feedback rule may include, for example, a message indicating lighting parameters for achieving a desired brightness in the shooting environment when the brightness is outside a predetermined range. The feedback rule may include, for example, transmitting a lighting control signal in a similar case, the lighting parameters for achieving a desired brightness in the shooting environment. The desired brightness may be predetermined or may be an estimated value. The estimated value for the desired brightness may be calculated, for example, by the first output control unit 432. The lighting to which this control signal is sent is lighting that affects the brightness of the shooting environment, and may be, for example, one or more predetermined lighting sources.

[0173] The feedback rule may include, for example, a message indicating focus parameters for a desired focus position when the focus position of the image capture device is operable and the iris image is out of focus. The feedback rule may include, for example, transmitting a control signal for the image capture device including focus parameters for a desired focus position in a similar case. The focus parameters are parameters related to the focus position of the image capture device. The desired focus position may be predetermined or may be an estimated value. The estimated value for the desired focus position may be calculated, for example, by the first output control unit 432. The image capture device to which this control signal is sent is an image capture device that captures an object, for example, a predetermined image capture device.

[0174] Although the control signal includes a parameter related to the brightness of the lighting and a focus parameter in the above example, the control signal may be a control signal for controlling a predetermined device other than the lighting or the image capture device. In other words, the feedback information may include a control signal for controlling a predetermined device.

[0175] A user may be a subject, an operator, or both.

[0176] The message may relate to a plurality of degradation factors. That is, for example, the first output control unit 432 may generate feedback information including a message for each of a plurality of degradation factors based on the deviation calculated by the deviation calculation unit 131 and a feedback rule. In this case, the first output control unit 432 may generate feedback information that notifies degradation factors in descending order of deviation. The first output control unit 432 may generate feedback information including messages for a predetermined number of degradation factors in descending order of deviation.

[0177] (Regarding the first display unit 433) When the feedback information includes a feedback screen, the first display unit 433 displays the feedback screen under the control of the first output control unit 432. Note that the first output information may include the first display screen, and in this case, the first display unit 433 may display the first display screen included in the first output information.

[0178] (Regarding the first speaker 434) When the feedback information includes feedback audio, the first speaker 434 outputs (emits) the feedback audio under the control of the first output control unit 432. Note that the first output information may include the first audio, and in this case, the first speaker 434 may output (emit) the first audio included in the first output information.

[0179] (Regarding the first communication unit 435) When the feedback information includes a control signal, the first communication unit 435, under the control of the first output control unit 432, transmits the control signal to a predetermined device in association with the control signal.

[0180] According to the present embodiment, the first output information includes feedback information for guiding the subject to improve the quality of the iris image, the feedback information being generated based on the deviation degree and a predetermined feedback rule regarding the deviation degree. The deviation degree indicates the degree of difference between the factor score calculated for each of the plurality of degradation factors and a predetermined threshold value.

[0181] This allows the quality of the iris image to be improved using the feedback information, making it easier to obtain a high-quality iris image that improves the accuracy of iris authentication.

[0182] Fifth Embodiment In this embodiment, an example in which second output information is output in addition to first output information will be described. Note that, for the sake of brevity, descriptions that overlap with other embodiments will be omitted as appropriate.

[0183] (Configuration example of information processing system S5 and information processing device 500) As shown in FIG. 19, the information processing system S5 and the information processing device 500 include an acquisition unit 110, a calculation unit 120, a first output unit 130, and a second output unit 540, which are similar to those in embodiment 1.

[0184] The second output unit 540 outputs second output information that associates at least one deterioration factor with a factor score corresponding to each of the at least one deterioration factor. The number of deterioration factors included in the second output information is smaller than the number of deterioration factors included in the first output information.

[0185] (Example of Processing Operation of Information Processing System S5 and Information Processing Device 500) The information processing system S5 and the information processing device 500 execute information processing as shown in FIG.

[0186] Steps S110, S120 and S130 are executed in the same manner as in the first embodiment.

[0187] The second output unit 540 outputs second output information in which at least one deterioration factor is associated with a factor score corresponding to each of the at least one deterioration factor (step S540). The number of deterioration factors included in the second output information is smaller than the number of deterioration factors included in the first output information.

[0188] (Regarding the Second Output Unit 540) The second output unit 540 outputs second output information. The number of deterioration factors included in the second output information is smaller than the number of deterioration factors included in the first output information. Such second output information may be output, for example, to a target. In contrast, the first output information may be output, for example, to an operator.

[0189] By referring to a large number of degradation factors and their factor scores, an operator can often more appropriately estimate degradation factors that need to be addressed in order to obtain a high-quality iris image that will improve the accuracy of iris authentication. In contrast, for a general target, even by referring to a large number of degradation factors and their factor scores, it may be difficult to estimate degradation factors that need to be addressed in order to obtain a high-quality iris image that will improve the accuracy of iris authentication. It may be easier to estimate degradation factors that need to be addressed in order to obtain a high-quality iris image that will improve the accuracy of iris authentication by referring to a smaller number of degradation factors and their factor scores. Therefore, by outputting different first output information and second output information that have different numbers of degradation factors, it becomes possible to more easily obtain a high-quality iris image that will improve the accuracy of iris authentication.

[0190] As shown in FIG. 21 , the second output unit 540 includes a second output control unit 542 , a second display unit 543 , and a second speaker 544 , for example.

[0191] The second output control unit 542 generates second output information that associates at least one deterioration factor with a factor score corresponding to each of the at least one deterioration factor. The second output control unit 542 generates the first output information, for example, using the factor score calculated for each of the multiple deterioration factors by the calculation unit 120. Furthermore, for example, the second output control unit 542 may generate the second output information by further using the deviation calculated for each of the multiple deterioration factors by the deviation calculation unit 131.

[0192] The second output information may include, for example, a second display screen and a second audio. The number of pairs of deterioration factors and factor scores included in each of the second display screen and the second audio may be smaller than the number of pairs of deterioration factors and factor scores included in each of the first display screen and the first audio. Except for this, the second display screen and the second audio may be configured similarly to the first display screen and the first audio, respectively.

[0193] (Second display unit 543) The second display unit 543 displays the second display screen included in the second output information under the control of the second output control unit 542. That is, outputting the second output information includes displaying the second display screen as the second output information.

[0194] (Second speaker 544) The second speaker 544 outputs the second sound included in the second output information under the control of the second output control unit 542. That is, outputting the second output information includes outputting (emitting) the second sound as the second output information.

[0195] The second output unit 540 may include only one of the second display unit 543 and the second speaker 544. In this case, the second output information may include only information of the second display screen and the second audio corresponding to either the second display unit 543 or the second speaker 544. The second output control unit 542 may control either the second display unit 543 or the second speaker 544.

[0196] As described above, according to this embodiment, the information processing system S5 includes the second output unit 540 that outputs second output information in which at least one deterioration factor is associated with a factor score corresponding to each of the at least one deterioration factor. The number of deterioration factors included in the second output information is smaller than the number of deterioration factors included in the first output information.

[0197] This makes it possible to output output information appropriate for different users, such as an operator and a target. Furthermore, it is possible for each different user to infer, from among multiple degradation factors, the degradation factor that needs to be addressed in order to acquire a high-quality iris image that improves the accuracy of iris authentication. Therefore, it becomes easier to acquire a high-quality iris image that improves the accuracy of iris authentication.

[0198] Sixth Embodiment In this embodiment, a description will be given of an example in which a plurality of iris images are acquired and a high-quality iris image is selected from the plurality of iris images. Note that, for the sake of brevity, descriptions that overlap with other embodiments will be omitted as appropriate.

[0199] (Configuration example of information processing system S6 and information processing device 600) As shown in FIG. 22 , the information processing system S6 and the information processing device 600 include an acquisition unit 110, a calculation unit 120, and a first output unit 130 similar to those in embodiment 1, a shooting instruction unit 640, a factor score storage unit 650, a quality score calculation unit 660, and a selection unit 670.

[0200] The photographing instruction unit 640 notifies the subject of predetermined photographing instructions for photographing the subject in different modes.

[0201] The factor score storage unit 650 stores a plurality of iris images acquired by the acquisition unit 110 in association with the factor scores for each deterioration factor calculated by the calculation unit 120 for each of the plurality of iris images.

[0202] The quality score calculation section 660 calculates, for each of the plurality of iris images, a quality score that indicates the degree of overall quality of the iris image.

[0203] The selector 670 selects one or more iris images from the plurality of iris images based on the quality scores.

[0204] (Example of Processing Operation of Information Processing System S6 and Information Processing Device 600) The information processing system S6 and the information processing device 600 execute information processing as shown in FIG.

[0205] The photographing instruction unit 640 notifies the subject of predetermined photographing instructions for photographing the subject in different modes (step S640).

[0206] Steps S110 and S120 are executed in the same manner as in the first embodiment.

[0207] The factor score storage unit 650 stores the plurality of iris images acquired in step S110 in association with the factor scores for each of the plurality of iris images calculated in step S120 for each deterioration factor (step S650).

[0208] Step S130 is executed in the same manner as in the first embodiment.

[0209] The quality score calculation unit 660 calculates a quality score indicating the degree of overall quality of each of the iris images (step S660).

[0210] The selection unit 670 selects one or more iris images from the plurality of iris images based on the quality scores (step S670).

[0211] (Regarding the photographing instruction unit 640) As described above, the photographing instruction unit 640 notifies the subject of a predetermined photographing instruction. This photographing instruction is, for example, an instruction to photograph the subject in different ways. In detail, for example, the instruction may be to orient the face toward the subject in each direction, such as the front, up, down, left, or right, in order to photograph the subject's iris from different directions. In this way, the acquisition unit 110 may acquire at least an iris image based on the subject image photographed in accordance with the photographing instruction. The photographing instruction may be notified to the subject by display or by sound.

[0212] (Regarding the factor score storage unit 650) The factor score storage unit 650 stores, for example, factor score information. The factor score storage unit 650 may be configured, for example, with a storage medium and a control unit that causes the storage medium to store the factor score information. The factor score information includes, for example, information that associates multiple iris images acquired by the acquisition unit 110 with the factor scores for each degradation factor calculated by the calculation unit 120 for each of the multiple iris images.

[0213] (Regarding the quality score calculation unit 660) The quality score calculation unit 660 calculates a quality score indicating the overall level of quality of each of the multiple iris images acquired by the acquisition unit 110, for example, by integrating the factor scores for each degradation factor.

[0214] The quality score calculation unit 660 acquires factor score information from, for example, the factor score storage unit 650. As a result, the quality score calculation unit 660 acquires a plurality of factor scores for a plurality of degradation factors for each of the plurality of iris images acquired by the acquisition unit 110.

[0215] The quality score calculation unit 660 calculates a quality score by integrating multiple factor scores for each of the multiple iris images. Methods for integrating multiple factor scores include adding up multiple factor scores, calculating an average of multiple factor scores, and calculating a weighted average of multiple factor scores. Calculating a weighted average is a calculation in which multiple factor scores are multiplied by a predetermined weight for each factor score and then added up. Note that the method for integrating multiple factor scores is not limited to the example given here. Furthermore, the quality score calculation unit 660 may calculate a quality score that indicates the overall level of quality of the iris image, and may calculate the quality score from the iris image. Examples of these methods will be described later.

[0216] (Regarding the selection unit 670) Based on the quality scores, the selection unit 670 selects one or more iris images from the multiple iris images acquired by the acquisition unit 110. The selection unit 670 may select, for example, the iris image with the highest quality score, or a predetermined number of iris images in descending order of quality score.

[0217] The selection unit 670 may select one or more iris images from the multiple iris images acquired by the acquisition unit 110 based on at least one of the quality score and the factor score. When the factor score is used, the selection unit 670 may select an iris image for which the factor scores corresponding to all of the degradation factors are equal to or greater than a threshold. The selection unit 670 may select an iris image for which the factor scores corresponding to all of the degradation factors are equal to or greater than a threshold and have the highest quality score. The selection unit 670 may select a predetermined number of iris images for which the factor scores corresponding to all of the degradation factors are equal to or greater than a threshold and have the highest quality score.

[0218] As described above, according to this embodiment, the information processing system S6 includes a photographing instruction unit 640, a factor score storage unit 650, a quality score calculation unit 660, and a selection unit 670. The photographing instruction unit 640 notifies a subject of predetermined photographing instructions for photographing the subject in different modes. The factor score storage unit 650 stores a plurality of acquired iris images in association with factor scores calculated for each of the plurality of iris images for each degradation factor. The quality score calculation unit 660 integrates the factor scores for each degradation factor for each of the plurality of iris images to calculate a quality score indicating the overall level of quality of the iris image. The selection unit 670 selects one or more iris images from the plurality of iris images based on the quality scores.

[0219] This makes it possible to acquire multiple iris images of a target captured in different ways and select one or more high-quality iris images from the multiple iris images, thereby making it easier to acquire high-quality iris images that improve the accuracy of iris authentication.

[0220] The quality score calculation unit 660 may calculate a quality score indicating the overall quality of the iris image. This quality score may be, for example, an authentication score in authentication using an iris image, or a score indicating authentication accuracy such as an error rate. The quality score may be calculated before outputting the first output information, and the first output information may include the quality score.

[0221] In this case, the quality score calculation unit 660 may include, for example, a machine learning model that estimates a quality score of an iris image using, as input, factor scores for each of a plurality of degradation factors related to the iris image. This machine learning model may be configured using, for example, a neural network. This machine learning model may be constructed by training using ground truth data including a plurality of factor scores and a quality score. The plurality of training factor scores may be, for example, a plurality of factor scores calculated by the calculation unit 120 for each of the plurality of training iris images.

[0222] Furthermore, for example, the quality score calculation unit 660 may include a machine learning model that receives an iris image as input and estimates the quality score of the iris image. This machine learning model may be configured using, for example, a neural network. This machine learning model may be constructed by training using ground truth data including multiple iris images for training and the quality scores of each iris image for training. These training iris images may be the same as the iris images used when the calculation unit 120 performs training.

[0223] In this way, if the quality score is a score that indicates the authentication accuracy, it is possible to select a high-quality iris image that can achieve high authentication accuracy in relation to the specific system that performs iris authentication. Therefore, it becomes possible to more easily obtain a high-quality iris image that further improves the accuracy of iris authentication.

[0224] [Embodiment 7] In the sixth embodiment, an example was described in which a plurality of iris images of a target photographed in different modes was acquired in accordance with a predetermined photographing instruction. In this embodiment, an example is described in which a plurality of iris images of a target photographed in different modes is acquired using first output information instead of a photographing instruction. Note that descriptions that overlap with other embodiments will be omitted as appropriate for the sake of brevity.

[0225] (Example of configuration of information processing system S7 and information processing device 700) As shown in FIG. 24 , the information processing system S7 and the information processing device 700 include an acquisition unit 110, a calculation unit 120, and a first output unit 130 similar to those in embodiment 1, and a factor score storage unit 650, a quality score calculation unit 660, and a selection unit 670 similar to those in embodiment 6.

[0226] 25 , steps S110 and S120 similar to those in the first embodiment, step S650 similar to those in the sixth embodiment, and step S130 similar to those in the first embodiment are repeated N times (step S670), where N is an integer equal to or greater than 2 and may be determined in advance.

[0227] Steps S660 and S670 are executed in the same manner as in the sixth embodiment.

[0228] As described above, according to this embodiment, by outputting the first output information, it is possible to acquire multiple iris images of a target captured in different ways. Then, it is possible to select one or more high-quality iris images from the multiple iris images. Therefore, it is possible to more easily acquire high-quality iris images that improve the accuracy of iris authentication.

[0229] (Modification 1) In the seventh embodiment, second output information may be used instead of the first output information.

[0230] This also achieves the same effect as in the seventh embodiment. That is, by outputting the second output information, it is possible to acquire multiple iris images of a target photographed in different ways. Then, it is possible to select one or more high-quality iris images from the multiple iris images. Therefore, it is possible to more easily acquire high-quality iris images that improve the accuracy of iris authentication.

[0231] (Modification 2) In the seventh embodiment, the information processing device 700 may further include a photography instruction unit 640, and a photography instruction and the first output information or the second output information may be used.

[0232] This also achieves the same effect as in the seventh embodiment. That is, by outputting a photographing instruction and the first output information or the second output information, it is possible to obtain multiple iris images of a target photographed in different ways. Then, it is possible to select one or more high-quality iris images from the multiple iris images. Therefore, it is possible to more easily obtain high-quality iris images that improve the accuracy of iris authentication.

[0233] (Variation 3) In the seventh embodiment, an example in which steps S110, S120, S650, and S130 are repeated N times has been described. However, the condition for ending the repetition of these processes (steps S110, S120, S650, and S130) is not limited to a predetermined number of times N.

[0234] For example, steps S110, S120, S650, and S130 may be repeatedly executed until an iris image in which factor scores corresponding to all degradation factors are equal to or greater than a threshold is obtained. Also, for example, steps S110, S120, S650, and S130 may be repeatedly executed until an iris image in which quality scores are equal to or greater than a predetermined quality threshold is obtained.

[0235] This also makes it possible to acquire multiple iris images of a target captured in different ways, and then select one or more high-quality iris images from the multiple iris images, making it easier to acquire high-quality iris images that improve the accuracy of iris authentication.

[0236] [Example of Factor Score Calculation Method] The factor scores of the degradation factors may be calculated using a general method. An example of a factor score calculation method will be described below. Note that the following description is not intended to limit the factor score calculation method.

[0237] (Regarding Contrast) The contrast may be one or both of the iris-sclera contrast and the iris-pupillary contrast. For example, the iris-sclera contrast may be calculated from the ratio of the sum and difference between the average luminance value of the iris region and the average luminance value of the sclera. For example, the iris-pupillary contrast may be calculated from the ratio of the difference between the average luminance value of the iris region and the average luminance value of the pupil region to the average luminance value of the pupil region. A median may be used instead of the average value. The target region for calculating the contrast may be, for example, an eye image or the iris region.

[0238] (Regarding Sharpness) Sharpness may be calculated by convolving a sharpness kernel with an image and calculating the sum of squares for each element of the convolved map. The target region for calculating sharpness may be, for example, an eye image or an iris region.

[0239] (Regarding Effective Iris Area) The area of ​​the iris region is, for example, the total number of pixels included in the iris region. The area of ​​the iris region may be the area obtained by subtracting the area of ​​the pupil region and the area obscured by eyeglass reflection, eyelashes, etc. from the area of ​​the outer circle of the iris region. The area of ​​the iris region may be the absolute value of the number of pixels, or may be a ratio obtained by dividing the area by the area of ​​the outer circle of the iris region.

[0240] (Regarding Brightness) The brightness factor score may be, for example, the average value, median value, top 1 / 4 value, bottom 1 / 4 value, etc. The target region for calculating the brightness factor score may be, for example, an eye image or an iris region.

[0241] (Regarding Pupil Dilation Rate) When the pupil and iris are considered to be circles (when parameters are estimated), the pupil dilation rate may be calculated using the radius of the pupil circle and the radius of the iris circle. The pupil dilation rate may be, for example, the ratio of the radius of the pupil circle to the radius of the iris circle. When the areas of the pupil and iris are estimated, the pupil dilation rate may be, for example, the ratio of the area of ​​the pupil region to the area of ​​the iris region.

[0242] Parameters representing the pupil and iris circles from the eye image may be directly estimated using a trained machine learning model. The areas of the pupil and iris may be calculated using parameters obtained when their shapes are estimated as circles. The areas of the pupil and iris may be calculated using segmentation results (segmentation maps) from the eye image.

[0243] (Regarding Grayscale Tone) Grayscale tone may be, for example, the entropy of the luminance values ​​of the entire image. Such grayscale tone may be, for example, the absolute value of the sum of Pi×logPi, where i=0 to 255, where Pi is the proportion of pixel value i contained in the entire image. The logarithmic function log has a base of 2.

[0244] (Regarding the ellipticity or circularity of the iris / pupil) The ellipticity or circularity of the iris / pupil may be, for example, the ratio of the minor axis to the major axis when the parameters (minor axis, major axis) are estimated assuming that the iris and pupil are each an ellipse.

[0245] (Regarding Margin from Image Edge) The margin from the image edge may be, for example, the shortest value among the shortest distances (margins from the image edge) between each point on the outer circle of the iris and the image edge.

[0246] (Regarding Eye Opening and Closing Degree) The eye opening and closing degree may be calculated using, for example, the vertical distance x between the centers of the upper and lower eyelids and the diameter r of the iris circle. In this case, the eye opening and closing degree may be calculated using, for example, min(1, x / r).

[0247] (Regarding the Degree of Focus Blur) The degree of focus blur may be estimated using a trained machine learning model, such as, but not limited to, a convolutional neural network model.

[0248] This machine learning model may be constructed, for example, by preparing a dataset of images with various degrees of focus blur, labeling each image with a degree of focus blur, and training the model to estimate labels of the degree of focus blur from the images.

[0249] The degree of focus blur may be, for example, a strength (standard deviation parameter σ) obtained by modeling focus blur with Gaussian blur. Specifically, for example, a training image dataset with a small degree of focus blur may be prepared. The machine learning model may then be constructed by learning to estimate the corresponding σ value by regression from an image in the training dataset to which a Gaussian blur of a certain strength (standard deviation parameter σ) has been applied. The strength σ of the Gaussian blur applied to the training data may be selected using a random number.

[0250] (Regarding the Degree of Motion Blur) The degree of motion blur may be estimated using a trained machine learning model, such as, but not limited to, a convolutional neural network model.

[0251] This machine learning model may be constructed, for example, by preparing a dataset of images with various degrees of motion blur, labeling each image with a degree of motion blur, and learning to estimate the labels of the degree of motion blur from the images.

[0252] The degree of motion blur may be, for example, the strength (kernel size) of a linear kernel modeled on motion blur. Specifically, a training image dataset with a small degree of motion blur may be prepared. The machine learning model may then be constructed by learning to estimate the size of a linear kernel by regression from an image in the training dataset to which a linear kernel of a certain strength (kernel size) has been applied. The size of the linear kernel applied to the training data may be selected using a random number.

[0253] (Regarding Estimation of the Glasses Reflection Region) The glasses reflection region may be estimated using a brightness threshold. For example, pixels having pixel values ​​greater than a predetermined threshold may be estimated as the glasses reflection region. This threshold may be, for example, the minimum value obtained by investigating the pixel values ​​of the glasses reflection region in multiple iris images prepared in advance.

[0254] The eyeglasses reflection region may be estimated using a histogram of the brightness values ​​of the image. For example, the top ⅛ or more of the pixels in the brightness value histogram may be estimated as the eyeglasses reflection region. Note that 1.8 here is merely an example and may be changed as appropriate. The eyeglasses reflection region may also be estimated using a general trained machine learning model. The machine learning model may be, for example, a convolutional neural network model, but is not limited to this. For example, a segmentation map of the reflection region may be estimated.

[0255] (Regarding Wearing or Not Wearing Glasses) Whether or not a person is wearing glasses may be detected using the glasses' reflection or the frames, which may cause the iris area or the area around the eyes to be obscured. Alternatively, whether or not a person is wearing glasses may be detected using a general trained machine learning model. The machine learning model may be, for example, a convolutional neural network model, but is not limited to this. For example, this machine learning model may be constructed by preparing an image dataset of people wearing glasses and an image dataset of people not wearing glasses, and training the model to classify whether or not glasses are being worn from the images.

[0256] (Regarding Wearing or Not of Hard Contact Lenses) Whether or not hard contact lenses are worn may be detected using a general trained machine learning model. The machine learning model may be, for example, a convolutional neural network model, but is not limited to this. The machine learning model may be constructed, for example, by preparing an image dataset with hard contact lenses worn and an image dataset without hard contact lenses worn, and training the model to classify the presence or absence of hard contact lenses from the images.

[0257] (Regarding Whether Colored Contacts are Wearing) Whether colored contacts are being worn may be detected by a method in which the hard contacts described above are replaced with colored contacts.

[0258] (Regarding Occlusion Fractions of Hair and Eyelashes) The occlusion fractions of hair and eyelashes may be estimated using a machine learning model. For example, a training image dataset with pre-annotated occlusion fractions may be prepared. Then, the machine learning model may be constructed by learning to directly estimate the occlusion fractions from images by regression.

[0259] For example, a training image dataset with pre-annotated occluded regions may be prepared, and a machine learning model may be constructed by learning to estimate a segmentation map of the occluded regions from the images. The percentage may be the ratio of the occluded area to the iris area from the estimated segmentation map.

[0260] Although the present disclosure has been described above with reference to the embodiments, the present disclosure is not limited to the above-described embodiments. Various modifications that can be understood by those skilled in the art can be made to the configuration and details of the present disclosure within the scope of the present disclosure. Furthermore, each embodiment can be combined with other embodiments as appropriate.

[0261] In addition, although the flowcharts used in the above description show a sequence of steps (processes), the order of steps executed in each embodiment is not limited to the sequence shown in the flowcharts. In each embodiment, the order of steps shown in the diagrams can be changed as long as it does not cause any problems in terms of the content.

[0262] Some or all of the above embodiments can be described as, but are not limited to, the following notes: 1. An information processing system comprising: an acquisition means for acquiring an iris image including an iris; a calculation means for using the acquired iris image to calculate, for each of a plurality of degradation factors indicating factors that degrade the quality of the iris image, a factor score indicating the degree of quality corresponding to the degradation factor; and a first output means for outputting first output information that associates the plurality of degradation factors with the factor scores corresponding to each of the plurality of degradation factors. 2. The information processing system described in 1., wherein outputting the first output information includes displaying a first display screen as the first output information, and the first display screen includes a score display area that associates the plurality of degradation factors with the factor scores corresponding to each of the plurality of degradation factors for each of the left and right eyes. 3. The score display area includes a score display diagram that represents the magnitude of the corresponding factor score for each of the plurality of degradation factors as the size of the area of ​​a figure of a predetermined shape, and the score display diagram includes a line indicating a predetermined threshold for each of the plurality of degradation factors. 4. The information processing system described in 3., in which the maximum value of the area of ​​the graphic corresponding to the factor score is determined according to the number of the plurality of degradation factors. 5. The information processing system described in 3. or 4., in which the position of the line indicating the threshold in the score display diagram is fixed or variable, the area of ​​the graphic representing the magnitude of the corresponding factor score is in accordance with the magnitude relative to a predetermined reference value for the factor score, and the reference value when the position of the line indicating the threshold is fixed is the predetermined threshold. 6. The information processing system described in any one of 3. to 5., in which the score display diagram represents the factor score in a different display mode depending on whether the factor score is within a predetermined range with respect to the predetermined threshold.7. The information processing system described in any one of 2. to 6., wherein the plurality of deterioration factors include at least one continuous deterioration factor whose factor score is expressed as a continuous value and at least one discrete deterioration factor whose factor score is expressed as a discrete value, and the score display area displays the corresponding factor score using different display modes for the continuous deterioration factor and the discrete deterioration factor. 8. The information processing system described in 2., wherein the score display area displays an image that associates the plurality of deterioration factors with a diagram showing changes over time in the factor score corresponding to each of the plurality of deterioration factors. 9. The information processing system described in any one of 1. to 8., further comprising estimation means that uses the acquired iris image to estimate key point positions that indicate positions of predetermined key points on the iris, and the calculation means calculates the factor score for each of the plurality of deterioration factors using the acquired iris image and the estimated key point positions. 10. 10. The information processing system of any one of 1. to 9., wherein the acquisition means acquires a target image captured by an imaging device of a target, and the first display screen includes an image display area showing the target image, and the image display area includes an iris guide showing a predetermined position where the iris of the target should be captured for at least one of the left and right eyes. 11. The information processing system of any one of 1. to 10., wherein the first output information includes feedback information for improving the quality of the iris image, generated based on a degree of deviation showing the degree of difference between the factor score calculated for each of the plurality of degradation factors and a predetermined threshold, and a feedback rule predetermined for the degree of deviation. 12. The information processing system of any one of 1. to 11., further comprising second output means for outputting second output information associating at least one degradation factor with the factor score corresponding to the at least one degradation factor, and wherein the number of degradation factors included in the second output information is smaller than the number of degradation factors included in the first output information.13. The information processing system described in any one of 1. to 12., further comprising: a photographing instruction means for notifying the subject of predetermined photographing instructions for photographing the subject in different modes; a factor score storage means for storing the acquired multiple iris images in association with a factor score for each of the multiple iris images calculated for each of the multiple iris images; a quality score calculation means for calculating, for each of the multiple iris images, a quality score indicating a degree of overall quality of the iris image; and a selection means for selecting one or more iris images from the multiple iris images based on the quality score. 14. An information processing device comprising: an acquisition means for acquiring an iris image including an iris; a calculation means for using the acquired iris image to calculate, for each of multiple degradation factors indicating a factor that degrades the quality of the iris image, a factor score indicating the degree of quality corresponding to the degradation factor; and a first output means for outputting first output information in association with the multiple degradation factors and the factor score corresponding to each of the multiple degradation factors. 15. The information processing device according to 14., wherein outputting the first output information includes displaying a first display screen as the first output information, and wherein the first display screen includes a score display area associating the plurality of deterioration factors with the factor scores corresponding to each of the plurality of deterioration factors for each of the left and right eyes. 16. The information processing device according to 15., wherein the score display area includes a score display diagram that represents the magnitude of the corresponding factor score for each of the plurality of deterioration factors by the area of ​​a figure having a predetermined shape, and the score display diagram includes a line indicating a predetermined threshold for each of the plurality of deterioration factors. 17. The information processing device according to 16., wherein the maximum area of ​​the figure corresponding to the factor score is determined according to the number of the plurality of deterioration factors. 18. The information processing device according to 16. or 17., wherein the position of the line indicating the threshold in the score display diagram is fixed or variable, the area of ​​the figure representing the magnitude of the corresponding factor score conforms to a size relative to a predetermined reference value for the factor score, and the reference value when the position of the line indicating the threshold is fixed is the predetermined threshold. The information processing device described in19. The information processing device according to any one of 16. to 18., wherein the score display diagram represents the factor score in a different display manner depending on whether the factor score is within a predetermined range with respect to a predetermined threshold. 20. The information processing device according to any one of 15. to 19., wherein the plurality of deterioration factors include at least one continuous deterioration factor whose factor score is represented by a continuous value and at least one discrete deterioration factor whose factor score is represented by a discrete value, and the score display area represents the corresponding factor score using different display manners for the continuous deterioration factor and the discrete deterioration factor. 21. The information processing device according to 15., wherein the score display area displays an image associating the plurality of deterioration factors with a diagram showing changes over time in the factor score corresponding to each of the plurality of deterioration factors. 22. The information processing device of any one of 14. to 21., further comprising: estimation means for estimating key point positions indicating positions of predetermined key points on the iris using the acquired iris image, wherein the calculation means calculates the factor score for each of the plurality of deterioration factors using the acquired iris image and the estimated key point positions. 23. The information processing device of any one of 14. to 22., wherein the acquisition means acquires a target image captured by an imaging device, wherein the first display screen includes an image display area showing the target image, and the image display area includes an iris guide indicating a predetermined position where the iris of the target should be reflected, for at least one of the left and right eyes. 24. The information processing device of any one of 14. to 23., wherein the first output information includes feedback information for improving the quality of the iris image, generated based on a degree of deviation indicating a degree of difference between the factor score calculated for each of the plurality of deterioration factors and a predetermined threshold, and a feedback rule related to the degree of deviation.25. The information processing device of any one of 14. to 24., further comprising second output means for outputting second output information that associates at least one of the degradation factors with the factor score corresponding to each of the at least one degradation factor, wherein the number of the degradation factors included in the second output information is smaller than the number of the degradation factors included in the first output information. 26. The information processing device of any one of 14. to 25., further comprising: photographing instruction means for notifying the subject of predetermined photographing instructions for photographing the subject in different modes; factor score storage means for storing the acquired multiple iris images in association with the factor score for each of the multiple iris images calculated for each of the multiple iris images; quality score calculation means for calculating, for each of the multiple iris images, a quality score that indicates the degree of overall quality of the iris image; and selection means for selecting one or more iris images from the multiple iris images based on the quality score. 27. 28. An information processing method in which one or more computers acquire an iris image including an iris, use the acquired iris image to calculate, for each of a plurality of degradation factors indicating factors that degrade the quality of the iris image, a factor score indicating the degree of quality corresponding to the degradation factor, and output first output information that associates the plurality of degradation factors with the factor scores corresponding to each of the plurality of degradation factors. 27. The information processing method described in 28., in which outputting the first output information includes displaying a first display screen as the first output information, and the first display screen includes a score display area that associates the plurality of degradation factors with the factor scores corresponding to each of the plurality of degradation factors for each of the left and right eyes. 29. The information processing method described in 28., in which the score display area includes a score display diagram that represents the magnitude of the corresponding factor score for each of the plurality of degradation factors as the size of the area of ​​a figure of a predetermined shape, and the score display diagram includes a line indicating a predetermined threshold for each of the plurality of degradation factors. 30. 29. The information processing method according to 28., wherein the maximum value of the area of ​​the graphic corresponding to the factor score is determined in accordance with the number of the plurality of degradation factors.31. The information processing method according to 29. or 30., wherein the position of the line indicating the threshold value in the score display diagram is fixed or variable, the area of ​​the figure indicating the magnitude of the corresponding factor score corresponds to a size relative to a predetermined reference value for the factor score, and the reference value when the position of the line indicating the threshold value is fixed is the predetermined threshold. 32. The information processing method according to any one of 29. to 31., wherein the score display diagram displays the factor score in a different display manner depending on whether the factor score is within a predetermined range with respect to the predetermined threshold. 33. The information processing method according to any one of 28. to 32., wherein the multiple deterioration factors include at least one continuous deterioration factor whose factor score is represented by a continuous value and at least one discrete deterioration factor whose factor score is represented by a discrete value, and the score display area displays the corresponding factor score using different display manners for the continuous deterioration factor and the discrete deterioration factor. 34. The information processing method according to any one of items 27 to 34, wherein the score display area displays an image associating the plurality of deterioration factors with a diagram showing changes over time in the factor scores corresponding to each of the plurality of deterioration factors. 35. The information processing method according to any one of items 27 to 34, further comprising: using the acquired iris image to estimate key point positions indicating positions of predetermined key points on the iris; and calculating the factor scores includes calculating the factor scores for each of the plurality of deterioration factors using the acquired iris image and the estimated key point positions. 36. The information processing method according to any one of items 27 to 35, wherein acquiring the iris image includes acquiring a target image captured by an imaging device of a target; the first display screen includes an image display area showing the target image; and the image display area includes an iris guide showing, for at least one of the left and right eyes, a predetermined position at which the iris of the target should be reflected.37. The information processing method described in any one of 27. to 36., wherein the first output information includes feedback information for improving the quality of the iris image, generated based on a degree of deviation indicating the degree of difference between the factor score calculated for each of the plurality of degradation factors and a predetermined threshold, and a feedback rule predetermined for the degree of deviation. 38. The information processing method described in any one of 27. to 37., further comprising outputting second output information that associates at least one degradation factor with the factor score corresponding to the at least one degradation factor, and wherein the number of degradation factors included in the second output information is smaller than the number of degradation factors included in the first output information. 39. The information processing method described in any one of 27. to 38., further comprising: notifying the subject of predetermined photographing instructions for photographing the subject in different modes; storing the acquired multiple iris images in association with the factor scores for each of the degradation factors calculated for each of the multiple iris images; calculating a quality score for each of the multiple iris images indicating a level of overall quality of the iris image; and selecting one or more iris images from the multiple iris images based on the quality score. 40. A program for causing one or more computers to execute the following steps: acquiring iris images including irises; using the acquired iris images, calculating factor scores indicating a level of quality corresponding to each of a multiple degradation factors that indicate factors that degrade the quality of the iris image; and outputting first output information associating the multiple degradation factors with the factor scores corresponding to each of the multiple degradation factors. 40. The program described in 40., wherein outputting the first output information includes displaying a first display screen as the first output information, and the first display screen includes a score display area that associates the plurality of deterioration factors with the factor scores corresponding to each of the plurality of deterioration factors for each of the left and right eyes.42. The program according to 41., wherein the score display area includes a score display diagram that represents the magnitude of the corresponding factor score for each of the plurality of deterioration factors as the size of the area of ​​a graphic of a predetermined shape, and the score display diagram includes a line indicating a predetermined threshold for each of the plurality of deterioration factors. 43. The program according to 42., wherein the maximum value of the area of ​​the graphic corresponding to the factor score is determined according to the number of the plurality of deterioration factors. 44. The program according to 42. or 43., wherein the position of the line indicating the threshold in the score display diagram is fixed or variable, wherein the area of ​​the graphic indicating the magnitude of the corresponding factor score corresponds to a size relative to a predetermined reference value for the factor score, and wherein the reference value when the position of the line indicating the threshold is fixed is the predetermined threshold. 45. The program according to any one of 42. to 44., wherein the score display diagram represents the factor score in a different display mode depending on whether the factor score is within a predetermined range relative to the predetermined threshold. 46. The program according to any one of 41. to 45., wherein the plurality of deterioration factors include at least one continuous deterioration factor whose factor score is expressed by a continuous value and at least one discrete deterioration factor whose factor score is expressed by a discrete value, and the score display area displays the corresponding factor score using different display modes for the continuous deterioration factor and the discrete deterioration factor. 47. The program according to 41., wherein the score display area displays an image associating the plurality of deterioration factors with a diagram showing changes over time in the factor score corresponding to each of the plurality of deterioration factors. 48. The program according to any one of 40. to 47., further comprising: using the acquired iris image to estimate key point positions indicating positions of predetermined key points on the iris; and calculating the factor score includes calculating the factor score for each of the plurality of deterioration factors using the acquired iris image and the estimated key point positions.49. The program described in any one of 40. to 48., wherein acquiring the iris image involves acquiring a target image captured by an imaging device of a target, the first display screen including an image display area showing the target image, and the image display area including an iris guide showing a predetermined position where the iris of the target should be captured for at least one of the left and right eyes. 50. The program described in any one of 40. to 49., wherein the first output information includes feedback information for improving the quality of the iris image, generated based on a degree of deviation indicating the degree of difference between the factor score calculated for each of the plurality of degradation factors and a predetermined threshold, and a feedback rule predetermined for the degree of deviation. 51. The program described in any one of 40. to 50., further including outputting second output information associating at least one of the degradation factors with the factor score corresponding to the at least one degradation factor, and wherein the number of degradation factors included in the second output information is smaller than the number of degradation factors included in the first output information. 52. The program according to any one of items 40 to 51, further comprising: notifying the target of predetermined photographing instructions for photographing the target in different modes; storing the acquired iris images in association with the factor scores for each of the degradation factors calculated for each of the plurality of iris images; calculating a quality score indicating the degree of overall quality of each of the plurality of iris images; and selecting one or more iris images from the plurality of iris images based on the quality score. 53. A recording medium having recorded thereon the program according to any one of items 40 to 52.

[0263] S1, S2, S4, S5, S6, S7 Information processing system 100, 200, 400, 500, 600, 700 Information processing device 110 Acquisition unit 120, 220 Calculation unit 130, 430 First output unit 131 Deviation calculation unit 132, 432 First output control unit 133, 433 First display unit 134, 434 First speaker 140, 240 Estimation unit 435 First communication unit 540 Second output unit 542 Second output control unit 543 Second display unit 544 Second speaker 640 Photography instruction unit 650 Factor score storage unit 660 Quality score calculation unit 670 Selection unit

Claims

1. An information processing system comprising: an acquisition means for acquiring an iris image including an iris; a calculation means for calculating, for each of a plurality of deterioration factors indicating factors for deteriorating the quality of the acquired iris image, a factor score indicating the degree of the quality corresponding to the deterioration factor using the acquired iris image; and a first output means for outputting first output information associating the plurality of deterioration factors with the factor scores corresponding to each of the plurality of deterioration factors.

2. Outputting the first output information includes displaying a first display screen as the first output information, and the first display screen includes a score display area associating the plurality of deterioration factors with the factor scores corresponding to each of the plurality of deterioration factors for the left and right eyes. The information processing system according to claim 1.

3. The score display area includes a score display diagram representing the magnitude of the corresponding factor score by the magnitude of the area of a figure having a predetermined shape for each of the plurality of deterioration factors, and the score display diagram includes a line indicating a predetermined threshold for each of the plurality of deterioration factors. The information processing system according to claim 2.

4. The maximum value of the area of the figure corresponding to the factor score is determined according to the number of the plurality of deterioration factors. The information processing system according to claim 3.

5. The position of the line indicating the threshold in the score display diagram is fixed or variable, the area of the figure representing the magnitude of the corresponding factor score follows the magnitude relative to a reference value predetermined for the factor score, and the reference value when the position of the line indicating the threshold is fixed is the predetermined threshold. The information processing system according to claim 3 or 4.

6. The score display diagram represents the factor score in different display modes according to whether the factor score is within a predetermined range with respect to a predetermined threshold. The information processing system according to any one of claims 3 to 5.

7. The plurality of deterioration factors include at least one continuous deterioration factor in which the factor score is represented by a continuous value and at least one discrete deterioration factor in which the factor score is represented by a discrete value, and the score display area represents the corresponding factor score using different display modes for the continuous deterioration factor and the discrete deterioration factor. The information processing system according to any one of claims 2 to 6.

8. The information processing system according to claim 2, wherein the score display area shows an image associating the plurality of deterioration factors with a diagram showing a change over time of the factor scores corresponding to each of the plurality of deterioration factors.

9. The information processing system according to any one of claims 1 to 8, further comprising estimation means for estimating a keypoint position indicating a position of a keypoint predetermined for the iris using the acquired iris image, wherein the calculation means calculates the factor score for each of the plurality of deterioration factors using the acquired iris image and the estimated keypoint position.

10. The information processing system according to any one of claims 1 to 9, wherein the acquisition means acquires a target image obtained by the imaging device capturing a target, the first display screen includes an image display area showing the target image, and the image display area includes an iris guide indicating a predetermined position where the iris of the target should be reflected for at least one of the left and right eyes.

11. The information processing system according to any one of claims 1 to 10, wherein the first output information includes feedback information for improving the quality of the iris image generated based on a degree of deviation indicating how different the factor score calculated for each of the plurality of deterioration factors is from a predetermined threshold value and a feedback rule predetermined for the degree of deviation.

12. The information processing system according to any one of claims 1 to 11, further comprising second output means for outputting second output information associating at least one of the deterioration factors with the factor score corresponding to each of the at least one deterioration factor, wherein the number of the deterioration factors included in the second output information is less than the number of the deterioration factors included in the first output information.

13. Imaging instruction means for notifying the subject of a predetermined imaging instruction for imaging the subject in different modes; factor score storage means for associating and storing the acquired plurality of iris images with the factor score for each of the deterioration factors calculated for each of the plurality of iris images; quality score calculation means for calculating, for each of the plurality of iris images, a quality score indicating the degree of the overall quality of the iris image; and selection means for selecting one or more iris images from among the plurality of iris images based on the quality score. The information processing system according to any one of claims 1 to 12.

14. Acquisition means for acquiring an iris image including an iris; calculation means for calculating, for each of a plurality of deterioration factors indicating factors that deteriorate the quality of the acquired iris image, a factor score indicating the degree of the quality corresponding to the deterioration factor, using the acquired iris image; and first output means for outputting first output information associating the plurality of deterioration factors with the factor scores corresponding to the respective plurality of deterioration factors. An information processing apparatus.

15. One or more computers acquire an iris image including an iris, calculate, for each of a plurality of deterioration factors indicating factors that deteriorate the quality of the acquired iris image, a factor score indicating the degree of the quality corresponding to the deterioration factor, using the acquired iris image, and output first output information associating the plurality of deterioration factors with the factor scores corresponding to the respective plurality of deterioration factors. An information processing method.

16. A recording medium having recorded thereon a program for causing one or more computers to acquire an iris image including an iris, calculate, for each of a plurality of deterioration factors indicating factors that deteriorate the quality of the acquired iris image, a factor score indicating the degree of the quality corresponding to the deterioration factor, using the acquired iris image, and output first output information associating the plurality of deterioration factors with the factor scores corresponding to the respective plurality of deterioration factors.

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