Iris image recognition method, device, computing equipment and medium

Abstract

The present disclosure provides an iris image recognition method, which relates to the technical fields of artificial intelligence, information security, etc. The method includes: receiving an iris image from a client, the iris image including multiple sub-region images; sorting the multiple sub-region images, and decrypting at least one of the multiple sub-region images to obtain multiple processed sub-region images; splicing the processed multiple sub-region images to obtain an iris image to be recognized; using a filter to perform image recognition on the iris image to be recognized to obtain texture feature data for the iris; based on the texture feature data, verifying the iris image to obtain a verification result, so as to send the verification result to the client. The present disclosure also provides an iris image recognition device, a computing device, a medium, and a program product.

Description

Technical Field

[0001] The present disclosure relates to technical fields such as artificial intelligence and information security, and in particular to an iris image recognition method, an iris image recognition device, a computing device, a computer-readable storage medium, and a computer program product. Background Art

[0002] As the application of iris recognition technology becomes increasingly widespread, there is a risk that iris data will be leaked during the cross-institutional transmission process during the iris recognition process. Therefore, how to ensure the security of iris data has become an urgent problem to be solved. In the process of iris recognition, the related technology changes the original features of the iris image or encrypts the iris image to ensure the security of the iris data. However, changing the original features of the iris image usually affects the recognition accuracy and may even make iris recognition unsuccessful. After the iris image is encrypted, it needs to be decrypted. The decrypted iris data is still at risk of being leaked, and the process of encrypting or decrypting the iris image results in a large amount of calculation and wastes computing resources. Summary of the invention

[0003] In view of this, the present disclosure provides an optimized iris image recognition method, an iris image recognition apparatus, a computing device, a computer-readable storage medium, and a computer program product.

[0004] One aspect of the present disclosure provides an iris image recognition method, comprising: receiving an iris image from a client, the iris image comprising a plurality of sub-region images; sorting the plurality of sub-region images, and decrypting at least one of the plurality of sub-region images to obtain a plurality of processed sub-region images; stitching the processed plurality of sub-region images to obtain an iris image to be recognized; performing image recognition on the iris image to be recognized using a filter to obtain texture feature data for the iris; and verifying the iris image based on the texture feature data to obtain a verification result, so as to send the verification result to the client.

[0005] According to an embodiment of the present disclosure, the method further includes, before receiving the iris image from the client: performing data communication with the client to obtain key information.

[0006] According to an embodiment of the present disclosure, the above-mentioned key information includes first key information, and the multiple sub-area images are arranged in sequence; the sorting processing of the multiple sub-area images includes: based on the first key information, changing the arrangement order of at least part of the multiple sub-area images.

[0007] According to an embodiment of the present disclosure, the above-mentioned key information includes second key information; the decryption processing of at least one sub-region image among the multiple sub-region images includes: based on the second key information, determining at least one sub-region image to be decrypted from the multiple sub-region images; and decrypting the at least one sub-region image to be decrypted.

[0008] According to an embodiment of the present disclosure, the filter includes a two-dimensional Gabor filter.

[0009] According to an embodiment of the present disclosure, the above-mentioned verification of the iris image based on the texture feature data to obtain a verification result includes: matching the texture feature data with reference feature data to obtain a matching result, wherein the reference feature data is feature data of a pre-stored reference iris image; and obtaining the verification result based on the matching result.

[0010] According to an embodiment of the present disclosure, the above method is executed by a server, the server is installed with a trusted execution environment, and the method is run by the server in the trusted execution environment.

[0011] Another aspect of the present disclosure provides an iris image recognition method, comprising: acquiring an iris image; dividing the iris image into a plurality of sub-region images, and arranging the plurality of sub-region images in sequence; changing the arrangement order of the plurality of sub-region images, and encrypting at least one of the plurality of sub-region images to obtain a plurality of processed sub-region images; sending the plurality of processed sub-region images to a server; and receiving a verification result from the server, wherein the verification result indicates whether the iris image has passed the verification.

[0012] According to an embodiment of the present disclosure, the method further includes, before collecting the iris image: performing data communication with the server to obtain key information.

[0013] According to an embodiment of the present disclosure, the above-mentioned key information includes first key information; the changing of the arrangement order of the multiple sub-region images includes: based on the first key information, changing the arrangement order of at least part of the multiple sub-region images.

[0014] According to an embodiment of the present disclosure, the above-mentioned key information includes second key information; the encryption processing of at least one sub-region image among the multiple sub-region images includes: based on the second key information, determining at least one sub-region image to be encrypted from the multiple sub-region images; and encrypting the at least one sub-region image to be encrypted.

[0015] Another aspect of the present disclosure provides an iris image recognition device, comprising: a first receiving module, a processing module, a splicing module, a recognition module and a verification module. The first receiving module is used to receive an iris image from a client, wherein the iris image includes a plurality of sub-region images; the processing module is used to sort the plurality of sub-region images, and to decrypt at least one of the plurality of sub-region images to obtain a plurality of processed sub-region images; the splicing module is used to splice the plurality of processed sub-region images to obtain an iris image to be recognized; the recognition module is used to perform image recognition on the iris image to be recognized using a filter to obtain texture feature data for the iris; the verification module is used to verify the iris image based on the texture feature data to obtain a verification result, so as to send the verification result to the client.

[0016] Another aspect of the present disclosure provides an iris image recognition device, comprising: an acquisition module, a division module, a change module, a sending module and a second receiving module. The acquisition module is used to acquire an iris image; the division module is used to divide the iris image into a plurality of sub-region images, and the plurality of sub-region images are arranged in sequence; the change module is used to change the arrangement order of the plurality of sub-region images, and encrypt at least one of the plurality of sub-region images to obtain a plurality of processed sub-region images; the sending module is used to send the plurality of processed sub-region images to a server; and the second receiving module is used to receive a verification result from the server, wherein the verification result indicates whether the iris image has passed the verification.

[0017] Another aspect of the present disclosure provides a computing device, comprising: one or more processors; a memory for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement: receiving an iris image from a client, the iris image comprising a plurality of sub-region images; sorting the plurality of sub-region images, and decrypting at least one of the plurality of sub-region images to obtain a plurality of processed sub-region images; stitching the processed plurality of sub-region images to obtain an iris image to be identified; performing image recognition on the iris image to be identified using a filter to obtain texture feature data for the iris; and verifying the iris image based on the texture feature data to obtain a verification result, so as to send the verification result to the client.

[0018] Another aspect of the present disclosure provides a computing device, comprising: one or more processors; a memory for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors are enabled to implement: acquiring an iris image; dividing the iris image into a plurality of sub-region images, and arranging the plurality of sub-region images in sequence; changing the arrangement order of the plurality of sub-region images, and encrypting at least one of the plurality of sub-region images to obtain a plurality of processed sub-region images; sending the plurality of processed sub-region images to a server; and receiving a verification result from the server, wherein the verification result indicates whether the iris image has passed the verification.

[0019] Another aspect of the present disclosure provides a non-volatile readable storage medium storing computer-executable instructions, which when executed are used to implement: receiving an iris image from a client, the iris image including a plurality of sub-region images; sorting the plurality of sub-region images, and decrypting at least one of the plurality of sub-region images to obtain a plurality of processed sub-region images; stitching the plurality of processed sub-region images to obtain an iris image to be identified; performing image recognition on the iris image to be identified using a filter to obtain texture feature data for the iris; and verifying the iris image based on the texture feature data to obtain a verification result, so as to send the verification result to the client.

[0020] Another aspect of the present disclosure provides a non-volatile readable storage medium storing computer executable instructions, which when executed are used to implement: acquiring an iris image; dividing the iris image into a plurality of sub-region images, and arranging the plurality of sub-region images in sequence; changing the arrangement order of the plurality of sub-region images, and encrypting at least one of the plurality of sub-region images to obtain a plurality of processed sub-region images; sending the plurality of processed sub-region images to a server; and receiving a verification result from the server, wherein the verification result indicates whether the iris image has passed the verification.

[0021] Another aspect of the present disclosure provides a computer program product, including a computer program, which, when executed by a processor, implements: receiving an iris image from a client, the iris image including a plurality of sub-region images; sorting the plurality of sub-region images, and decrypting at least one of the plurality of sub-region images to obtain a plurality of processed sub-region images; stitching the plurality of processed sub-region images to obtain an iris image to be identified; performing image recognition on the iris image to be identified using a filter to obtain texture feature data for the iris; and verifying the iris image based on the texture feature data to obtain a verification result, so as to send the verification result to the client.

[0022] Another aspect of the present disclosure provides a computer program product, including a computer program, which, when executed by a processor, implements: collecting an iris image; dividing the iris image into a plurality of sub-region images, wherein the plurality of sub-region images are arranged in sequence; changing the arrangement order of the plurality of sub-region images, and encrypting at least one of the plurality of sub-region images to obtain a plurality of processed sub-region images; sending the plurality of processed sub-region images to a server; and receiving a verification result from the server, wherein the verification result indicates whether the iris image has passed the verification.

[0023] According to the embodiments of the present disclosure, the iris image recognition method as described above can at least partially solve the technical problems in the related art that the iris data has the risk of being leaked, the encryption or decryption process of the iris image has a large amount of calculation and wastes computing resources. Therefore, the security of the iris data and the technical effect of reducing the resource consumption of processing the iris data can be achieved. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] For a more complete understanding of the present disclosure and its advantages, reference will now be made to the following description taken in conjunction with the accompanying drawings, in which:

[0025] Figure 1 The system architecture of the iris image recognition method and the iris image recognition device according to the embodiments of the present disclosure is schematically shown;

[0026] Figure 2 The flowchart of the iris image recognition method according to the embodiment of the present disclosure is schematically shown;

[0027] Figure 3 The flowchart of the iris image recognition method according to another embodiment of the present disclosure is schematically shown;

[0028] Figure 4 A timing diagram schematically shows data interaction between a client and a server according to an embodiment of the present disclosure;

[0029] Figure 5 A schematic diagram schematically shows image division according to an embodiment of the present disclosure;

[0030] Figure 6 A schematic diagram of out-of-order processing according to an embodiment of the present disclosure is schematically shown;

[0031] Figure 7 The block diagram of the iris image recognition device according to the embodiment of the present disclosure is schematically shown;

[0032] Figure 8 A block diagram schematically shows an iris image recognition device according to another embodiment of the present disclosure; and

[0033] Fig. 9 The block diagram schematically shows a computing device for implementing iris image recognition according to an embodiment of the present disclosure. DETAILED DESCRIPTION

[0034] Hereinafter, embodiments of the present disclosure will be described with reference to the accompanying drawings. However, it should be understood that these descriptions are exemplary only and are not intended to limit the scope of the present disclosure. In the following detailed description, for ease of explanation, many specific details are set forth to provide a comprehensive understanding of the embodiments of the present disclosure. However, it is apparent that one or more embodiments may also be implemented without these specific details. In addition, in the following description, descriptions of known structures and technologies are omitted to avoid unnecessary confusion of the concepts of the present disclosure.

[0035] The terms used herein are only for describing specific embodiments and are not intended to limit the present disclosure. The terms "comprise", "include", etc. used herein indicate the existence of the features, steps, operations and / or components, but do not exclude the existence or addition of one or more other features, steps, operations or components.

[0036] All terms (including technical and scientific terms) used herein have the meanings commonly understood by those skilled in the art, unless otherwise defined. It should be noted that the terms used herein should be interpreted as having a meaning consistent with the context of this specification, and should not be interpreted in an idealized or overly rigid manner.

[0037] When using expressions such as "at least one of A, B, and C, etc.", they should generally be interpreted according to the meaning of the expression commonly understood by those skilled in the art (for example, "a system having at least one of A, B, and C" should include but is not limited to a system having A alone, B alone, C alone, A and B, A and C, B and C, and / or A, B, C, etc.).

[0038] Some block diagrams and / or flow charts are shown in the accompanying drawings. It should be understood that some blocks or combinations thereof in the block diagrams and / or flow charts may be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable control device, so that these instructions, when executed by the processor, may create a device for implementing the functions / operations described in these block diagrams and / or flow charts.

[0039] Therefore, the technology of the present disclosure can be implemented in the form of hardware and / or software (including firmware, microcode, etc.). In addition, the technology of the present disclosure can take the form of a computer program product on a computer-readable storage medium storing instructions, which can be used by an instruction execution system or in combination with an instruction execution system. In the context of the present disclosure, a computer-readable storage medium can be any medium that can contain, store, transmit, propagate, or transmit instructions. For example, a computer-readable storage medium can include, but is not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, device, or propagation medium. Specific examples of computer-readable storage media include: magnetic storage devices, such as magnetic tapes or hard disks (HDDs); optical storage devices, such as compact disks (CD-ROMs); memories, such as random access memories (RAMs) or flash memory; and / or wired / wireless communication links.

[0040] An embodiment of the present disclosure provides an iris image recognition method executed by a server, comprising: receiving an iris image from a client, the iris image comprising a plurality of sub-region images; sorting the plurality of sub-region images, and decrypting at least one of the plurality of sub-region images to obtain a plurality of processed sub-region images; stitching the processed plurality of sub-region images to obtain an iris image to be recognized; performing image recognition on the iris image to be recognized using a filter to obtain texture feature data for the iris; and verifying the iris image based on the texture feature data to obtain a verification result, so as to send the verification result to the client.

[0041] An embodiment of the present disclosure provides an iris image recognition method executed by a client, comprising: collecting an iris image; dividing the iris image into multiple sub-region images, and arranging the multiple sub-region images in sequence; changing the arrangement order of the multiple sub-region images, and encrypting at least one sub-region image among the multiple sub-region images to obtain multiple processed sub-region images; sending the processed multiple sub-region images to a server; and receiving a verification result from the server, wherein the verification result indicates whether the iris image has passed the verification.

[0042] Figure 1 The system architecture of the iris image recognition method and the iris image recognition device according to the embodiment of the present disclosure is schematically shown. It should be noted that: Figure 1What is shown is merely an example of a system architecture to which the embodiments of the present disclosure can be applied, in order to help those skilled in the art understand the technical content of the present disclosure, but it does not mean that the embodiments of the present disclosure cannot be used in other devices, systems, environments or scenarios.

[0043] like Figure 1 As shown, the system architecture 100 according to this embodiment may include a server 110, a client 120, and a network 130. The network 130 is used to provide a medium for a communication link between the client 120 and the server 110. The network 130 may include various connection types, such as wired, wireless communication links, or optical fiber cables.

[0044] The user can use the client 120 to interact with the server 110 through the network 130 to receive or send messages, etc. Various communication client applications can be installed on the client 120, such as shopping applications, web browser applications, search applications, instant messaging tools, email clients, social platform software, etc. (only as examples).

[0045] The client 120 may be any electronic device having a display screen and supporting web browsing, including but not limited to a smart phone, a tablet computer, a laptop computer, a desktop computer, and the like.

[0046] The server 110 may be a server that provides various services, such as a background management server that provides support for websites browsed by users using the client 120 (for example only). The background management server may analyze and process received data such as user requests, and feed back processing results (such as web pages, information, or data obtained or generated according to user requests) to the terminal device. The server 110 may be a server deployed in the cloud.

[0047] In the embodiment of the present disclosure, the client 120 has, for example, a camera 121, and the client 120 can collect an iris image through the camera 121, and then process the collected iris image, and send the processed iris image to the server 110, so that the server 110 can recognize the iris image to obtain a recognition result. The server then returns the recognition result to the client 120.

[0048] In the embodiment of the present disclosure, a trusted execution environment 111 is installed in the server 110 , for example. The trusted execution environment 111 is also called a TEE (Trusted Execution Environment) environment.

[0049] The trusted execution environment 111 is a separate "area" at the chip level, which provides a more secure place for code execution and data storage. This independent area is difficult to be obtained by other programs from the software or hardware layer, thereby ensuring its confidentiality and non-tamperability.

[0050] Therefore, after the client 120 sends the iris image to the server 110, the server stores the iris image in the trusted execution environment 111, and performs image recognition and other related processing on the iris image in the trusted execution environment 111 to ensure the security of the iris image.

[0051] It should be understood that Figure 1 The number of clients, networks and servers in the embodiment is only for illustration. Any number of clients, networks and servers may be provided as required.

[0052] The following combination Figure 1 The system architecture is based on Figure 2 to Figure 6 The iris image recognition method of the embodiment of the present disclosure is described.

[0053] Figure 2 The flowchart of the iris image recognition method according to the embodiment of the present disclosure is schematically shown.

[0054] like Figure 2 As shown, the iris image recognition method of the embodiment of the present disclosure may include, for example, operations S210 to S250. Figure 1 The client is shown to execute.

[0055] In operation S210, an iris image is acquired.

[0056] In the embodiment of the present disclosure, the client has, for example, a camera, and the iris image is collected through the camera.

[0057] In operation S220, the iris image is divided into a plurality of sub-region images, and the plurality of sub-region images are arranged in sequence.

[0058] According to the embodiment of the present disclosure, after the client divides the iris image into a plurality of sub-region images, the plurality of sub-region images have an arrangement order, and the plurality of sub-region images can be reassembled according to the arrangement order to obtain the original iris image.

[0059] In operation S230, the arrangement order of the plurality of sub-region images is changed, and at least one of the plurality of sub-region images is encrypted to obtain a plurality of processed sub-region images.

[0060] In an embodiment of the present disclosure, the client performs shuffling and encryption processing on multiple sub-region images. The shuffling may be performed first and then the encryption, or the encryption may be performed and then the shuffling. The multiple sub-region images after shuffling ensure that it is difficult to reassemble the multiple sub-region images to obtain an iris image after the multiple sub-region images are leaked, thereby ensuring the security of the iris image. In addition, some of the sub-region images in the multiple sub-region images may be encrypted. For example, when the multiple sub-region images include 16 sub-regions, 4 of the sub-region images may be encrypted respectively to ensure that after the multiple sub-region images are leaked, the original iris image cannot be obtained based on the encrypted sub-region images, thereby ensuring the security of the iris image.

[0061] In addition, encrypting some sub-region images among multiple sub-region images can not only ensure the security of the iris image, but also reduce the amount of calculation for image encryption and subsequent decryption, further improving the image encryption efficiency and subsequent decryption efficiency.

[0062] In operation S240, the processed plurality of sub-region images are transmitted to a server.

[0063] For example, the multiple sub-region images that have been subjected to shuffle processing and encryption processing are sent to the server, so that the server can process the multiple sub-region images and perform image verification on the multiple sub-region images to obtain verification results.

[0064] In operation S250, a verification result is received from the server, where the verification result indicates whether the iris image has passed the verification.

[0065] In the embodiment of the present disclosure, after the client collects the iris image, in order to ensure the security of the iris image, the iris image is divided into multiple sub-region images, and then the multiple sub-region images are shuffled and some of the sub-region images are encrypted. Then the processed multiple sub-region images are sent to the server for iris recognition verification. It can be seen that the technical solution of the embodiment of the present disclosure can not only ensure the security of the client transmitting the iris image to the server, but also reduce the resource consumption of image processing.

[0066] Figure 3 The flowchart of the iris image recognition method according to another embodiment of the present disclosure is schematically shown.

[0067] like Figure 3 As shown, the iris image recognition method of the embodiment of the present disclosure may include, for example, operations S310 to S350. Figure 1 to execute on the server shown.

[0068] In operation S310, an iris image is received from a client, where the iris image includes a plurality of sub-region images.

[0069] In an embodiment of the present disclosure, the multiple sub-region images from the client are, for example, subjected to shuffling and encryption processing by the client.

[0070] In operation S320, a sorting process is performed on the plurality of sub-region images, and a decryption process is performed on at least one of the plurality of sub-region images to obtain a plurality of processed sub-region images.

[0071] In the disclosed embodiment, after the server receives the multiple sub-region images, the multiple sub-region images may be sorted and decrypted. The sorting process may be performed first and then the decryption process, or the decryption process may be performed first and then the sorting process. After the multiple sub-region images are sorted and decrypted, the obtained multiple sub-region images may be spliced ​​into the original iris image. The decryption process of the multiple sub-region images may be the decryption process of part of the sub-regions, and the part of the sub-region images may be, for example, the sub-region images encrypted by the client.

[0072] In operation S330, the processed multiple sub-region images are stitched together to obtain an iris image to be recognized.

[0073] After the multiple sub-region images are sorted and decrypted, the processed multiple sub-region images can be spliced ​​to obtain an original iris image, and the obtained original iris image is used as the iris image to be recognized.

[0074] In operation S340, the filter is used to perform image recognition on the iris image to be recognized, so as to obtain texture feature data of the iris.

[0075] In operation S350, the iris image is verified based on the texture feature data to obtain a verification result, so as to send the verification result to the client.

[0076] In the embodiment of the present disclosure, the filter is, for example, a two-dimensional Gabor filter, which is a relatively effective texture detection tool. After extracting the texture feature data of the iris through the two-dimensional Gabor filter, the texture feature data is processed to verify whether the iris image passes the verification, and the verification result is sent to the client.

[0077] In the embodiment of the present disclosure, after receiving the multiple sub-region images that have been shuffled and encrypted from the client, the server sorts the multiple sub-region images and decrypts some of the sub-region images. Then, the processed multiple sub-region images are spliced ​​to obtain the iris image to be identified. Next, the iris image to be identified is image recognized and verified to confirm whether the iris image has passed the verification. It can be seen that the technical solution of the embodiment of the present disclosure can not only ensure the security of the iris image during transmission, but also reduce the resource consumption of iris image processing.

[0078] In another embodiment of the present disclosure, a server is installed with a trusted execution environment. After receiving multiple sub-region images, the server can store the multiple sub-region images in the trusted execution environment to ensure the security of the iris image. In addition, the server can perform sorting, encryption, splicing, image recognition, and image verification on the images in the trusted execution environment to ensure the security of the iris image during the processing.

[0079] Figure 4 The diagram schematically shows a timing diagram of data interaction between a client and a server according to an embodiment of the present disclosure.

[0080] like Figure 4 As shown, the client performs operations S410A to S470A, and the server performs operations S410B to S490B.

[0081] In operation S410A, before collecting the iris image, the client communicates with the server to obtain key information.

[0082] In operation S410B, before receiving the iris image from the client, the server performs data communication with the client to obtain key information.

[0083] In the embodiment of the present disclosure, the client and the server perform handshake in advance so that both parties negotiate and determine the key information subsequently used for iris image processing.

[0084] In operation S420A, an iris image is acquired.

[0085] In operation S430A, the iris image is divided into a plurality of sub-region images.

[0086] In operation S440A, at least one sub-region image among the plurality of sub-region images is encrypted based on the key information.

[0087] In an embodiment of the present disclosure, the key information includes, for example, first key information and second key information. The first key information represents a sequence rule for performing random processing on multiple sub-region images. The second key information represents at least one sub-region image that needs to be encrypted among the multiple sub-region images. In one example, the first key information includes a digital string, and the second key information includes a digital string, and the digital string of the first key information and the digital string of the second key information can be the same.

[0088] For example, when performing encryption processing, at least one sub-region image to be encrypted is determined from multiple sub-region images based on the second key information, and then the at least one sub-region image to be encrypted is encrypted. For example, each sub-region image to be encrypted is encrypted using a symmetric encryption algorithm. Exemplarily, the symmetric encryption algorithm includes, for example, an SM4 algorithm.

[0089] In operation S450A, the arrangement order of the plurality of sub-region images is changed based on the key information,

[0090] In an embodiment of the present disclosure, the arrangement order of at least some of the sub-region images in the plurality of sub-region images is changed based on the first key information. For example, the first key information includes a digital string, wherein the digital string represents, for example, a transformation rule of the sub-region images.

[0091] In operation S460A, the processed plurality of sub-region images are sent to a server.

[0092] In operation S420B, an iris image is received from a client, where the iris image includes a plurality of sub-region images.

[0093] In an embodiment of the present disclosure, after receiving the multiple sub-region images, the server stores the received multiple sub-region images in a trusted execution environment to ensure the security of the iris image.

[0094] In operation S430B, a sorting process is performed on the plurality of sub-region images based on the key information.

[0095] In an embodiment of the present disclosure, before the multiple sub-region images are shuffled by the client, the order of the multiple sub-region images is, for example, sub-region image A, sub-region image B, and sub-region image C. After the multiple sub-region images are shuffled by the client, the arrangement order becomes, for example, sub-region image B, sub-region image A, and sub-region image C.

[0096] The first key information, for example, indicates that the client has swapped the order of sub-region image A and sub-region image B. Therefore, the arrangement order of the multiple sub-region images received by the server is: sub-region image B, sub-region image A, sub-region image C. Based on the first key information, the server changes the arrangement order of at least some of the multiple sub-region images, for example, changes the arrangement order of sub-region image A and sub-region image B, and obtains the arrangement order of the multiple sub-region images as: sub-region image A, sub-region image B, sub-region image C.

[0097] In operation S440B, at least one sub-region image among the plurality of sub-region images is decrypted based on the key information.

[0098] In the embodiment of the present disclosure, the second key information, for example, indicates that the client has encrypted sub-region image C among sub-region image A, sub-region image B, and sub-region image C. Then, based on the second key information, the server can determine sub-region image C from multiple sub-region images as at least one sub-region image to be decrypted, and then decrypt the at least one sub-region image to be decrypted.

[0099] In operation S450B, the processed multiple sub-region images are stitched together to obtain an iris image to be recognized.

[0100] After the server performs sorting and decryption processing on the multiple sub-region images, the server performs image splicing processing on the multiple sub-region images to obtain a complete image as the iris image to be recognized.

[0101] In operation S460B, the filter is used to perform image recognition on the iris image to be recognized, and texture feature data for the iris is obtained.

[0102] In the embodiments of the present disclosure, the texture feature data is, for example, a feature vector. For example, a complex-valued two-dimensional Gabor filter under polar coordinates is used to extract the features of the iris details from the normalized iris image, and 1024 wavelets are used to process the iris image to obtain a 2048-bit, i.e., 256-byte, encoding, thereby obtaining a feature vector of the iris.

[0103] In operation S470B, the texture feature data and the reference feature data are matched to obtain a matching result.

[0104] In operation S480B, a verification result is obtained based on the matching result, and the verification result indicates whether the iris image passes the verification.

[0105] In an embodiment of the present disclosure, the reference feature data is feature data of a pre-stored reference iris image. The texture feature data and the reference feature data are both feature vectors, for example. The Euclidean distance between the two feature vectors is calculated as a matching result. If the Euclidean distance is less than a preset distance value, it means that the two match, and it is considered that the collected iris image and the pre-stored iris image are of the same user. At this time, the verification result indicates that the collected iris image has passed the verification.

[0106] In operation S490B, the server sends the verification result to the client.

[0107] In operation S470A, the client receives the verification result from the server.

[0108] Figure 5 A schematic diagram of image division according to an embodiment of the present disclosure is schematically shown.

[0109] like Figure 5 As shown, after the client acquires the iris image 500, it divides the iris image into a plurality of sub-region images, for example, into 16 sub-region images. The 16 sub-region images are numbered, for example, a, b, c, d, e, f, g, 1, 2, 3, 4, 5, 6, 7, 8, 9 from left to right and from top to bottom. The numbering is only for example, and an irregular numbering method may be selected, so that after multiple sub-region images are leaked, an illegal user cannot know the order of the sub-region images by their numbers, thereby preventing an illegal user from splicing multiple sub-region images to obtain the original image.

[0110] Figure 6 The figure schematically shows a schematic diagram of out-of-order processing according to an embodiment of the present disclosure.

[0111] like Figure 6 As shown, after the client divides the iris image, multiple sub-region images 610 are obtained, and the arrangement order of the multiple sub-region images 610 is, for example, a, b, c, d, e, f, g, 1, 2, 3, 4, 5, 6, 7, 8, 9.

[0112] In the embodiment of the present disclosure, the first key information and the second key information are both represented by a digital string "2685", for example.

[0113] For example, some of the sub-region images among the plurality of sub-region images are encrypted based on the second key information. For example, based on the numbers in the digital string "2685", the 2nd, 6th, 8th, and 5th sub-region images are encrypted. The numbers of the 2nd, 6th, 8th, and 5th sub-region images are "b", "f", "1", and "e", respectively.

[0114] Next, the plurality of sub-region images 610 are subjected to a first shuffle process to obtain a first process result 620. For example, based on "2685", the first bit value "2" is determined as the transformation step length, and the sub-region images at odd positions of the plurality of sub-region images 610 are sequentially transformed with the sub-region images to the right thereof according to the transformation step length "2" from left to right.

[0115] For example, for the sub-region image at odd position 1, determine the sub-region image at position 3 to the right according to the transformation step "2", and exchange the sub-region image "a" at odd position 1 with the sub-region image "c" at position 3. For the sub-region image at odd position 3, determine the sub-region image at position 5 to the right according to the transformation step "2", and exchange the sub-region image "a" at odd position 3 with the sub-region image "e" at position 5. For the sub-region image at odd position 5, determine the sub-region image at position 7 to the right according to the transformation step "2", and exchange the sub-region image "a" at odd position 5 with the sub-region image "g" at position 7. And so on, until all the sub-region images at odd positions are traversed.

[0116] In addition, when the sum of the position digit and the transformation step size of a sub-region image at an odd position exceeds the total number of sub-region images, the sub-region image at the odd position will not be moved. For example, if the sum of the position digit "15" and the transformation step size "2" of the sub-region image at the odd position 15 is 17, which is greater than the total number of sub-region images 16, the sub-region image at the odd position 15 will not be exchanged.

[0117] Next, the first processing result 620 is subjected to a second shuffle process to obtain a second processing result 630. For example, based on "2685", the second digit value "6" is determined as the transformation step length, and the sub-region images at odd positions in the first processing result 620 are transformed with the sub-region images to the right thereof in sequence from left to right according to the transformation step length "6".

[0118] For example, for the sub-region image at odd position 1, determine the sub-region image at position 7 to the right according to the transformation step "6", and swap the sub-region image "c" at odd position 1 with the sub-region image "2" at position 7. Swap the sub-region image "e" at odd position 3 with the sub-region image "4" at position 9. And so on, until all the sub-region images at odd positions are traversed. When the sum of the position digit and the transformation step of a sub-region image at an odd position exceeds the total number of sub-region images, the sub-region image at the odd position is not swapped.

[0119] Next, the second processing result 630 is subjected to a third shuffle process to obtain a third processing result 640. For example, based on "2685", the third digit value "8" is determined as the transformation step length, and the sub-region images at even positions in the second processing result 630 are transformed with the sub-region images to the right thereof in sequence from left to right according to the transformation step length "8".

[0120] For example, for the sub-region image at the even position 2, determine the sub-region image at position 10 to the right according to the transformation step "8", and swap the sub-region image "b" at the even position 2 with the sub-region image "3" at position 10. Swap the sub-region image "d" at the even position 4 with the sub-region image "5" at position 12. And so on, until all the sub-region images at the even positions are traversed. When the sum of the position digit and the transformation step of a sub-region image at an even position exceeds the total number of sub-region images, the sub-region image at the even position will not be swapped.

[0121] Next, the third processing result 640 is subjected to a fourth shuffle process to obtain a fourth processing result 650. For example, based on "2685", the fourth digit value "5" is determined as the change step size, and the sub-region images at even positions in the third processing result 640 are transformed with the sub-region images to the right thereof in sequence from left to right according to the transformation step size "5".

[0122] For example, for the sub-region image at the even position 2, determine the sub-region image at the position 7 to the right according to the transformation step "5", and swap the sub-region image "3" at the even position 2 with the sub-region image "8" at the position 7. Swap the sub-region image "5" at the even position 4 with the sub-region image "a" at the position 9. And so on, until all the sub-region images at the even positions are traversed. When the sum of the position digit and the transformation step of a sub-region image at an even position exceeds the total number of sub-region images, the sub-region image at the even position is not swapped.

[0123] It can be seen that the final processing result is obtained after four random processings are performed on multiple sub-region images based on the digital string "2685". The first two random processings are for sub-region images at odd positions, and the last two random processings are for sub-region images at even positions.

[0124] Then, the client sends the encrypted and randomized sub-region images to the server. The arrangement order of the sub-region images received by the server is consistent with the arrangement order of the sub-region images in the fourth processing result 650.

[0125] Then, the server reorders the received multiple sub-region images. For example, for the fourth processing result 650, the sub-region images at the even positions are determined from right to left, and the determined sub-region images at the even positions are exchanged with the sub-region images at the right of them with a transformation step of "5". For example, for the fourth processing result 650, the sub-region image "e" at the even position 10 is determined from right to left, and the sub-region image "b" at the position 15 is determined to the right according to the transformation step of "5", and the sub-region image "e" at the odd position 10 is exchanged with the sub-region image "b" at the position 15, and the third processing result 640 is obtained by reverse transformation. When the sum of the position digit and the transformation step of the determined sub-region image at the even position exceeds the total number of sub-region images, the sub-region image at the even position is not transformed. For example, when the sum of the determined even-numbered sub-region image position digit "12" and the transformation step "5" is 17 and exceeds the total number of sub-region images 16, the sub-region image at the even position "12" is not exchanged.

[0126] It can be seen that the server reverses the fourth processing result 650 based on the digital string "2685" to obtain the third processing result 640, reverses the third processing result 640 to obtain the second processing result 630, reverses the second processing result 630 to obtain the first processing result 620, and reverses the first processing result 620 to obtain the original multiple sub-region images 610. Then, based on the digital string "2685", some of the sub-region images in the multiple sub-region images 610 are decrypted. For example, the 2nd, 6th, 8th, and 5th sub-region images are decrypted. The numbers of the 2nd, 6th, 8th, and 5th sub-region images are "b", "f", "1", and "e", respectively.

[0127] According to the embodiment of the present disclosure, the partner client uses an image segmentation algorithm to split the complete iris image, shuffle it, and partially encrypt it before transmitting it to the cloud server. The cloud server implements sub-region image decryption, image sorting, and image splicing in a trusted execution environment based on key information, as well as completes iris feature extraction and matching calculations. On the one hand, by dividing, shuffling, and partially encrypting the iris image by the partner client, the difficulty of generating a counterfeit iris image is increased, thereby reducing the risk of the original iris image being leaked during network transmission; at the same time, the method of encrypting some sub-region images reduces the computational overhead of encrypting and decrypting the entire image, and reduces the subsequent running time of the decryption algorithm in the trusted execution environment. On the other hand, the cloud server performs image restoration and feature extraction and comparison calculations through the iris recognition service in the trusted execution environment. The trusted execution environment ensures that the complete original iris image is not obtained and stored by illegal users, prevents the iris image from being illegally accessed or leaked by database attacks, and ensures the privacy and security of the iris collected by the partner client.

[0128] Figure 7 The block diagram of the iris image recognition device according to the embodiment of the present disclosure is schematically shown.

[0129] like Figure 7 As shown, the iris image recognition device 700 may include, for example, a first receiving module 710 , a processing module 720 , a splicing module 730 , a recognition module 740 , and a verification module 750 .

[0130] The first receiving module 710 may be used to receive an iris image from a client, where the iris image includes a plurality of sub-region images. Figure 3 The operation S310 described above will not be described in detail here.

[0131] The processing module 720 may be used to sort the multiple sub-region images and decrypt at least one of the multiple sub-region images to obtain the processed multiple sub-region images. Figure 3 The operation S320 described above will not be described in detail here.

[0132] The stitching module 730 may be used to stitch the processed multiple sub-region images to obtain an iris image to be recognized. According to an embodiment of the present disclosure, the stitching module 730 may, for example, perform the above-mentioned Figure 3 The operation S330 described above will not be described in detail here.

[0133] The recognition module 740 can be used to perform image recognition on the iris image to be recognized by using a filter to obtain texture feature data for the iris. According to the embodiment of the present disclosure, the recognition processing 740 can, for example, perform the above reference Figure 3 The operation S340 described above will not be described in detail here.

[0134] The verification module 750 can be used to verify the iris image based on the texture feature data to obtain a verification result, so as to send the verification result to the client. According to the embodiment of the present disclosure, the second verification module 750 can, for example, execute the above reference Figure 3 The operation S350 described above will not be described in detail here.

[0135] Figure 8 The block diagram of an iris image recognition device according to another embodiment of the present disclosure is schematically shown.

[0136] like Figure 8 As shown, the iris image recognition device 800 may include, for example, a collection module 810 , a division module 820 , a modification module 830 , a sending module 840 and a second receiving module 850 .

[0137] The acquisition module 810 may be used to acquire an iris image, where the iris image includes multiple sub-region images. Figure 2 The operation S210 described above will not be described in detail here.

[0138] The division module 820 may be used to divide the iris image into a plurality of sub-region images, and the plurality of sub-region images are arranged in sequence. According to an embodiment of the present disclosure, the division module 820 may, for example, execute the above reference Figure 2 The operation S220 described above will not be described in detail here.

[0139] The modification module 830 may be used to modify the arrangement order of the plurality of sub-region images, and to perform encryption processing on at least one of the plurality of sub-region images to obtain the processed plurality of sub-region images. Figure 2 The operation S230 described above will not be described in detail here.

[0140] The sending module 840 may be used to send the processed multiple sub-region images to the server. According to the embodiment of the present disclosure, the sending module 840 may, for example, execute the above reference Figure 2 The operation S240 described above will not be described in detail here.

[0141] The second receiving module 850 may be used to receive a verification result from the server, wherein the verification result indicates whether the iris image has passed the verification. Figure 2 The operation S250 described above will not be described in detail here.

[0142] According to the embodiments of the present invention, any one or more of the modules, submodules, units, and subunits, or at least part of the functions of any one of them can be implemented in one module. According to the embodiments of the present invention, any one or more of the modules, submodules, units, and subunits can be split into multiple modules for implementation. According to the embodiments of the present invention, any one or more of the modules, submodules, units, and subunits can be at least partially implemented as hardware circuits, such as field programmable gate arrays (FPGAs), programmable logic arrays (PLAs), systems on chips, systems on substrates, systems on packages, application specific integrated circuits (ASICs), or can be implemented by hardware or firmware in any other reasonable way of integrating or packaging the circuit, or implemented in any one of the three implementation methods of software, hardware, and firmware, or in any appropriate combination of any of them. Alternatively, according to the embodiments of the present invention, one or more of the modules, submodules, units, and subunits can be at least partially implemented as computer program modules, and when the computer program modules are run, the corresponding functions can be performed.

[0143] For example, any multiple of the first receiving module 710, the processing module 720, the splicing module 730, the identification module 740, and the verification module 750 (or the acquisition module 810, the division module 820, the change module 830, the sending module 840, and the second receiving module 850) can be combined into one module for implementation, or any one of the modules can be split into multiple modules. Alternatively, at least part of the functions of one or more of these modules can be combined with at least part of the functions of other modules and implemented in one module. According to an embodiment of the present disclosure, at least one of the first receiving module 710, the processing module 720, the splicing module 730, the identification module 740 and the verification module 750 (or the acquisition module 810, the division module 820, the change module 830, the sending module 840 and the second receiving module 850) can be at least partially implemented as a hardware circuit, such as a field programmable gate array (FPGA), a programmable logic array (PLA), a system on a chip, a system on a substrate, a system on a package, an application-specific integrated circuit (ASIC), or can be implemented by hardware or firmware such as any other reasonable way of integrating or packaging the circuit, or can be implemented in any one of the three implementation methods of software, hardware and firmware or in an appropriate combination of any of them. Alternatively, at least one of the first receiving module 710, the processing module 720, the splicing module 730, the identification module 740 and the verification module 750 (or the acquisition module 810, the division module 820, the change module 830, the sending module 840 and the second receiving module 850) can be at least partially implemented as a computer program module, which can perform corresponding functions when the computer program module is executed.

[0144] Fig. 9 The block diagram schematically shows a computing device for implementing iris image recognition according to an embodiment of the present disclosure. Fig. 9 The computing device shown is only an example and should not bring any limitation to the functionality and scope of use of the embodiments of the present disclosure.

[0145] like Fig. 9 As shown, the computing device 900 includes a processor 901 and a computer-readable storage medium 902. The computing device 900 can execute the method according to the embodiment of the present disclosure.

[0146] Specifically, the processor 901 may include, for example, a general-purpose microprocessor, an instruction set processor and / or a related chipset and / or a special-purpose microprocessor (e.g., an application-specific integrated circuit (ASIC)), etc. The processor 901 may also include an onboard memory for cache purposes. The processor 901 may be a single processing unit or multiple processing units for performing different actions of the method flow according to an embodiment of the present disclosure.

[0147] Computer readable storage medium 902, for example, can be any medium capable of containing, storing, conveying, propagating or transmitting instructions. For example, readable storage media can include, but are not limited to, electrical, magnetic, optical, electromagnetic, infrared or semiconductor systems, devices, devices or propagation media. Specific examples of readable storage media include: magnetic storage devices, such as magnetic tapes or hard disks (HDD); optical storage devices, such as compact disks (CD-ROMs); memory, such as random access memory (RAM) or flash memory; and / or wired / wireless communication links.

[0148] The computer-readable storage medium 902 may include a computer program 903 , which may include codes / computer-executable instructions, which when executed by the processor 901 cause the processor 901 to perform a method according to an embodiment of the present disclosure or any variation thereof.

[0149] The computer program 903 may be configured to have, for example, a computer program code including a computer program module. For example, in an exemplary embodiment, the code in the computer program 903 may include one or more program modules, for example, including 903A, module 903B, ... It should be noted that the division method and number of modules are not fixed, and those skilled in the art may use appropriate program modules or program module combinations according to actual conditions, and when these program module combinations are executed by the processor 901, the processor 901 may execute the method according to the embodiment of the present disclosure or any variation thereof.

[0150] According to an embodiment of the present disclosure, at least one of the first receiving module 710, the processing module 720, the splicing module 730, the identification module 740, and the verification module 750 (or the acquisition module 810, the division module 820, the modification module 830, the sending module 840, and the second receiving module 850) can be implemented as a reference. Fig. 9 The computer program modules described herein, when executed by the processor 901, can implement the corresponding operations described above.

[0151] The present disclosure also provides a computer-readable storage medium, which may be included in the device / apparatus / system described in the above embodiments; or may exist independently without being assembled into the device / apparatus / system. The above computer-readable storage medium carries one or more programs, and when the above one or more programs are executed, the above method is implemented.

[0152] According to an embodiment of the present disclosure, a computer-readable storage medium may be a computer-readable signal medium or a computer-readable storage medium or any combination of the two. A computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to, an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present disclosure, a computer-readable storage medium may be any tangible medium containing or storing a program that may be used by or in conjunction with an instruction execution system, device or device. In the present disclosure, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, in which a computer-readable program code is carried. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. The computer-readable signal medium may also be any computer-readable storage medium other than a computer-readable storage medium, which may send, propagate or transmit a program for use by or in conjunction with an instruction execution system, apparatus or device. The program code contained on the computer-readable storage medium may be transmitted using any appropriate medium, including but not limited to: wireless, wired, optical cable, radio frequency signal, etc., or any suitable combination of the above.

[0153] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, functions and operations of the system, method and computer program product according to various embodiments of the present disclosure. In this regard, each box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the above-mentioned module, program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flow chart and the combination of boxes in the block diagram or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0154] It will be appreciated by those skilled in the art that the features described in the various embodiments and / or claims of the present disclosure may be combined and / or combined in a variety of ways, even if such combinations and / or combinations are not explicitly described in the present disclosure. In particular, the features described in the various embodiments and / or claims of the present disclosure may be combined and / or combined in a variety of ways without departing from the spirit and teachings of the present disclosure. All of these combinations and / or combinations fall within the scope of the present disclosure.

[0155] Although the present disclosure has been shown and described with reference to specific exemplary embodiments of the present disclosure, it should be understood by those skilled in the art that various changes in form and details may be made to the present disclosure without departing from the spirit and scope of the present disclosure as defined by the appended claims and their equivalents. Therefore, the scope of the present disclosure should not be limited to the above-mentioned embodiments, but should be determined not only by the appended claims, but also by the equivalents of the appended claims.

Claims

1. An iris image recognition method, comprising: Performing data communication with a client to obtain key information, wherein the key information includes first key information and second key information, the first key information represents a transformation rule for performing four shuffle processes on a plurality of sub-region images, the second key information represents at least one sub-region image that needs to be encrypted among the plurality of sub-region images, the first two shuffle processes of the four shuffle processes are for sub-region images at odd positions, and the last two shuffle processes of the four shuffle processes are for sub-region images at even positions; receiving an iris image from the client, the iris image comprising the plurality of sub-region images, wherein the plurality of sub-region images are numbered in an irregular manner by the client, the transformation rule is determined based on the first key information, a random order is performed according to the transformation rule, at least one sub-region image to be encrypted is determined from the plurality of sub-region images based on the second key information, and at least one sub-region image among the plurality of sub-region images is encrypted and then sent; Sorting the plurality of sub-region images, and decrypting at least one of the plurality of sub-region images to obtain a plurality of processed sub-region images; Performing image stitching on the processed multiple sub-region images to obtain an iris image to be identified; Using a filter to perform image recognition on the iris image to be recognized, to obtain texture feature data for the iris; and Based on the texture feature data, verify the iris image to obtain a verification result, so as to send the verification result to the client; The method is executed by a server, a trusted execution environment is installed on the server, and the method is run by the server in the trusted execution environment.

2. The method according to claim 1, wherein: The multiple sub-region images are arranged in sequence; and the sorting process of the multiple sub-region images comprises: Based on the first key information, the arrangement order of at least part of the sub-region images among the plurality of sub-region images is changed.

3. The method according to claim 1, wherein: The decrypting process of at least one sub-region image among the plurality of sub-region images comprises: Based on the second key information, determining at least one sub-region image to be decrypted from the plurality of sub-region images; and Decryption processing is performed on the at least one sub-region image to be decrypted.

4. The method according to claim 1, wherein: The filter comprises a two-dimensional Gabor filter.

5. The method according to claim 1, wherein: The verifying the iris image based on the texture feature data to obtain a verification result comprises: Matching the texture feature data with reference feature data to obtain a matching result, wherein the reference feature data is feature data of a pre-stored reference iris image; and Based on the matching result, the verification result is obtained.

6. An iris image recognition method, comprising: Performing data communication with a server to obtain key information, wherein the key information includes first key information and second key information, the first key information represents a transformation rule for performing four shuffle processes on a plurality of sub-region images, the second key information represents at least one sub-region image that needs to be encrypted among the plurality of sub-region images, the first two shuffle processes of the four shuffle processes are for sub-region images at odd positions, and the last two shuffle processes of the four shuffle processes are for sub-region images at even positions; Collecting iris images; Dividing the iris image into a plurality of sub-region images and numbering them in an irregular manner, wherein the plurality of sub-region images are arranged in sequence; Determining the transformation rule based on the first key information, changing the arrangement order of the multiple sub-region images according to the transformation rule, and determining at least one sub-region image to be encrypted from the multiple sub-region images based on the second key information, encrypting at least one sub-region image among the multiple sub-region images, and obtaining multiple processed sub-region images; The processed multiple sub-region images are sent to a server, so that the server performs the following operations after receiving the multiple sub-region images: Sorting the plurality of sub-region images, and decrypting at least one of the plurality of sub-region images to obtain a plurality of processed sub-region images; Performing image stitching on the processed multiple sub-region images to obtain an iris image to be identified; Using a filter to perform image recognition on the iris image to be recognized, to obtain texture feature data for the iris; and Based on the texture feature data, verifying the iris image to obtain a verification result; and receiving the verification result from the server, wherein the verification result indicates whether the iris image passes the verification; The server is installed with a trusted execution environment, and the operation method executed by the server after receiving the multiple sub-region images is run by the server in the trusted execution environment.

7. The method according to claim 6, wherein: The changing of the arrangement order of the plurality of sub-region images comprises: Based on the first key information, the arrangement order of at least part of the sub-region images among the plurality of sub-region images is changed.

8. The method according to claim 6, wherein: The encrypting process of at least one sub-region image among the plurality of sub-region images comprises: Based on the second key information, determining at least one sub-region image to be encrypted from the plurality of sub-region images; Encryption processing is performed on the at least one sub-region image to be encrypted.

9. An iris image recognition device, comprising: A first communication module, used to perform data communication with a client to obtain key information, wherein the key information includes first key information and second key information, the first key information represents a transformation rule for performing four shuffle processes on a plurality of sub-region images, the second key information represents at least one sub-region image that needs to be encrypted among the plurality of sub-region images, the first two shuffle processes of the four shuffle processes are for sub-region images at odd positions, and the last two shuffle processes of the four shuffle processes are for sub-region images at even positions; a first receiving module, configured to receive an iris image from the client, the iris image comprising the plurality of sub-region images, wherein the plurality of sub-region images are numbered in an irregular manner by the client, the transformation rule is determined based on the first key information, random processing is performed based on the transformation rule, at least one sub-region image to be encrypted is determined from the plurality of sub-region images based on the second key information, and at least one sub-region image among the plurality of sub-region images is encrypted and then sent; A processing module, used for sorting the multiple sub-region images and decrypting at least one sub-region image among the multiple sub-region images to obtain multiple processed sub-region images; A stitching module, used for stitching the processed multiple sub-region images to obtain an iris image to be recognized; Recognition processing, for performing image recognition on the iris image to be recognized by using a filter to obtain texture feature data for the iris; and A verification module, configured to verify the iris image based on the texture feature data to obtain a verification result, so as to send the verification result to the client; The device is arranged in a server, a trusted execution environment is installed in the server, and the functions executed by the device are run by the server in the trusted execution environment.

10. An iris image recognition device, comprising: a second communication module, configured to perform data communication with the server to obtain key information, wherein the key information includes first key information and second key information, the first key information representing a transformation rule for performing four shuffle processes on a plurality of sub-region images, the second key information representing at least one sub-region image that needs to be encrypted among the plurality of sub-region images, the first two shuffle processes of the four shuffle processes being performed on sub-region images at odd positions, and the last two shuffle processes of the four shuffle processes being performed on sub-region images at even positions; A collection module, used for collecting iris images; A division module, used for dividing the iris image into a plurality of sub-region images and numbering them in an irregular manner, wherein the plurality of sub-region images are arranged in sequence; a changing module, configured to determine the transformation rule based on the first key information, change the arrangement order of the plurality of sub-region images according to the transformation rule, and determine at least one sub-region image to be encrypted from the plurality of sub-region images based on the second key information, encrypt at least one sub-region image among the plurality of sub-region images, and obtain a plurality of processed sub-region images; A sending module is used to send the processed multiple sub-region images to a server, so that the server performs the following operations after receiving the multiple sub-region images: Sorting the plurality of sub-region images, and decrypting at least one of the plurality of sub-region images to obtain a plurality of processed sub-region images; Performing image stitching on the processed multiple sub-region images to obtain an iris image to be identified; Using a filter to perform image recognition on the iris image to be recognized, to obtain texture feature data for the iris; and Based on the texture feature data, verifying the iris image to obtain a verification result; and A second receiving module is used to receive the verification result from the server, wherein the verification result indicates whether the iris image passes the verification; The server is installed with a trusted execution environment, and the operation method executed by the server after receiving the multiple sub-region images is run by the server in the trusted execution environment.

11. A computing device comprising: one or more processors; a memory for storing one or more programs, When the one or more programs are executed by the one or more processors, the one or more processors implement the method according to any one of claims 1 to 5.

12. A computing device comprising: one or more processors; a memory for storing one or more programs, When the one or more programs are executed by the one or more processors, the one or more processors implement the method according to any one of claims 6 to 8.

13. A computer-readable storage medium storing computer-executable instructions, wherein the instructions are used to implement the method according to any one of claims 1 to 5 when executed.

14. A computer-readable storage medium storing computer-executable instructions, wherein the instructions are used to implement the method according to any one of claims 6 to 8 when executed.

15. A computer program product comprising computer executable instructions for implementing the method according to any one of claims 1 to 5 when the instructions are executed.

16. A computer program product comprising computer executable instructions for implementing the method according to any one of claims 6 to 8 when the instructions are executed.

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