Safety authentication method and device based on iris recognition, equipment, medium and product

Abstract

The invention discloses a security authentication method, device and equipment based on iris recognition, a medium and a product. The method comprises the following steps: in response to a security authentication request of a target user, acquiring a sample picture set of the target user through an image acquisition device; performing segmentation processing on each sample picture in the sample picture set through a masking technology algorithm to obtain each iris template matched with each sample picture; processing each iris template based on a preset feature fusion algorithm to obtain an iris feature vector matched with the target user; and searching whether a target vector matched with the iris feature vector exists in a pre-established iris feature database, and performing security authentication on the target user according to a matching result. Through the technical scheme of the invention, the iris-based security identification of the target user can be realized, the security authentication operation cost is reduced, the accuracy of the security authentication result is improved, and the security of the system is further improved.

Description

Technical Field

[0001] The present invention relates to the field of biometrics, and in particular to a security authentication method, device, equipment, medium and product based on iris recognition. Background Art

[0002] With the widespread application of the Internet of Things (IoT) in business and life, it has shown great potential in industries such as Internet banking, healthcare, and transportation. However, the IoT faces severe challenges in terms of security. Especially in Internet banking, for the processing of sensitive data, a powerful and high-performance security system is urgently needed to ensure the secure connection between IoT clients and servers.

[0003] At present, biometric technology has become one of the main means to deal with this threat. Fingerprint recognition, iris recognition and voiceprint recognition are used as cards or tokens to verify the identity and connection security in the Internet of Things. However, there are many problems with the existing biometric technology used to verify the secure connection of the Internet of Things. First of all, it is expensive, and accurate verification often relies on more complex classification algorithms and additional hardware support. In the field of identity authentication and authorization, single-modal recognition systems show a high error rate and poor authentication accuracy, resulting in low authentication accuracy. In order to solve these problems of single-modal recognition systems, the industry currently generally adopts multi-modal biometric technology. However, this method requires additional hardware equipment investment, and the classification algorithm is more complex, which undoubtedly increases the cost and complexity of the system.

[0004] In summary, the existing security authentication methods supported by biometric technology have the problems of high security authentication operation costs and low accuracy of security authentication results. Summary of the invention

[0005] The present invention provides a security authentication method, device, equipment, medium and product based on iris recognition, which can solve the problems of high security authentication operation cost and low accuracy of security authentication results of existing security authentication methods supported by biometric technology.

[0006] In a first aspect, an embodiment of the present invention provides a security authentication method based on iris recognition, the method comprising:

[0007] In response to a security authentication request of a target user, collecting a sample picture set of the target user through an image acquisition device, wherein the sample picture set includes two pictures of the target user including left-eye images and two pictures including right-eye images;

[0008] Segmenting each sample image in the sample image set by using a masking technology algorithm to obtain iris templates that match each sample image;

[0009] Processing each iris template based on a preset feature fusion algorithm to obtain an iris feature vector matching the target user;

[0010] A search is performed in a pre-established iris feature database to determine whether there is a target vector that matches the iris feature vector, and security authentication is performed on the target user based on the matching result.

[0011] In a second aspect, an embodiment of the present invention provides a security authentication device based on iris recognition, the device comprising:

[0012] A sample collection module, configured to collect a sample picture set of the target user through an image collection device in response to a security authentication request of the target user, wherein the sample picture set includes two pictures of the target user including a left eye image and two pictures including a right eye image;

[0013] An image segmentation module is used to segment each sample image in the sample image set by using a masking technology algorithm to obtain iris templates that match each sample image;

[0014] A feature fusion module, used to process each iris template based on a preset feature fusion algorithm to obtain an iris feature vector matching the target user;

[0015] The security authentication module is used to search in a pre-established iris feature database whether there is a target vector that matches the iris feature vector, and to perform security authentication on the target user according to the matching result.

[0016] In a third aspect, an embodiment of the present invention provides an electronic device, the electronic device comprising:

[0017] at least one processor; and

[0018] a memory communicatively connected to the at least one processor; wherein,

[0019] The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute a security authentication method based on iris recognition as described in any embodiment of the present invention.

[0020] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement a security authentication method based on iris recognition as described in any embodiment of the present invention when executed.

[0021] In a fifth aspect, an embodiment of the present invention provides a computer program product, which includes a computer program. When the computer program is executed by a processor, it implements a security authentication method based on iris recognition as described in any embodiment of the present invention.

[0022] The technical solution of the embodiment of the present invention first responds to the security authentication request of the target user, collects the sample picture set of the target user through the image acquisition device, then segments each sample picture in the sample picture set through the masking technology algorithm to obtain each iris template matching each sample picture, then processes each iris template based on a preset feature fusion algorithm to obtain an iris feature vector matching the target user, finally searches a pre-established iris feature database for whether there is a target vector matching the iris feature vector, and performs security authentication on the target user according to the matching result, thereby solving the problem that the security authentication operation cost of the existing security authentication method supported by biometric technology is high and the accuracy of the security authentication result is low, and realizes the secure identification of the target user based on the iris, reduces the security authentication operation cost while improving the accuracy of the security authentication result, thereby improving the security of the system.

[0023] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present invention, nor are they intended to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0025] Figure 1 is a flow chart of a security authentication method based on iris recognition provided according to the first embodiment of the present invention;

[0026] Figure 2 is a flow chart of a security authentication method based on iris recognition provided according to Embodiment 2 of the present invention;

[0027] Figure 3 is a structural diagram of a security authentication device based on iris recognition provided according to Embodiment 3 of the present invention;

[0028] Figure 4 It is a structural schematic diagram of an electronic device for implementing a security authentication method based on iris recognition according to an embodiment of the present invention. DETAILED DESCRIPTION

[0029] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0030] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, any variation of the terms "including" and "having" is intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0031] Embodiment 1

[0032] Figure 1 A flowchart of a security authentication method based on iris recognition is provided in Embodiment 1 of the present invention. This embodiment is applicable to the situation where security authentication of a target user is performed based on the iris. The method can be executed by a security authentication device based on iris recognition. The security authentication device based on iris recognition can be implemented in the form of hardware and / or software. The security authentication device based on iris recognition can be configured in a terminal or server with a security authentication function based on iris recognition.

[0033] like Figure 1 As shown, the method includes:

[0034] S110 . In response to a security authentication request of a target user, a sample picture set of the target user is collected by an image collection device.

[0035] The sample picture set includes two pictures of the target user including left-eye images and two pictures including right-eye images.

[0036] Specifically, when the target user initiates a security authentication request, the system will respond in a timely manner. The security authentication request refers to a request from the user to the system to confirm the legitimacy of his or her identity in order to obtain a certain permission or perform a specific operation. For example, the operation of a user entering a password when making an online payment can be regarded as a security authentication request. At this time, the system uses advanced image acquisition devices to collect sample picture sets of the target user. The prime image acquisition device can be a high-definition camera, 3D scanner and other equipment. For example, common mobile phone front cameras or professional face recognition scanners are image acquisition devices.

[0037] It should be noted that the sample image set includes two images of the target user that focus on the left eye image, and two images that focus on the right eye image. This specific collection of eye images is intended to improve the accuracy and reliability of security authentication through precise analysis of eye features.

[0038] S120 , performing segmentation processing on each sample image in the sample image set by using a masking technology algorithm to obtain each iris template that matches each sample image.

[0039] The masking technology algorithm is an algorithm strategy used to highlight specific areas and mask irrelevant parts in image processing. In this embodiment, it can be used to segment the eye image in the sample image to obtain an iris template.

[0040] Among them, the method of segmenting each sample image in the sample image set through a masking technology algorithm to obtain each iris template that matches each sample image respectively includes: performing grayscale processing and smoothing filtering processing on each sample image in the sample image set to obtain each processed sample image; and processing each processed sample image respectively through a pre-configured image processing algorithm to obtain an iris template that matches each sample image respectively.

[0041] Specifically, the grayscale processing can be used to convert a color image into a grayscale image, reduce the interference of color information, and make subsequent processing more focused on the brightness changes of the image. The smoothing filter processing can be used to remove noise in the image to make the image smoother and clearer. For example, the common Gaussian smoothing filter can effectively reduce salt and pepper noise in the image.

[0042] Furthermore, each processed sample image is processed by a preconfigured image processing algorithm to obtain an iris template that matches each sample image, including: performing edge detection on each sample image based on an edge detection algorithm to obtain iris edge data that matches each sample image; performing masking processing on each sample image using a preset masking algorithm based on each iris edge data to obtain each masked iris image; and using a threshold segmentation method to segment each masked iris image to obtain each iris template that matches each sample image.

[0043] Among them, the edge detection algorithm in this embodiment can be a Canny edge detection algorithm, which can be used to capture the part of the image where the grayscale value changes significantly, so as to determine the edge position of the iris; further, the threshold segmentation method is to divide the image into different areas by setting a specific grayscale value threshold. In this embodiment, the content containing the iris can be segmented from other content in the masked iris image to obtain an iris template that only includes the iris content.

[0044] S130: Process each iris template based on a preset feature fusion algorithm to obtain an iris feature vector matching the target user.

[0045] S140: Searching a pre-established iris feature database to see whether there is a target vector matching the iris feature vector, and performing security authentication on the target user according to the matching result.

[0046] Specifically, a search is performed in a pre-established iris feature database to determine whether there is a target vector that matches the iris feature vector, and security authentication is performed on the target user based on the matching result, including: calculating the similarity between the iris feature vector and each feature vector in the iris feature database, and verifying whether there is a target vector in the iris feature database whose similarity is greater than a preset similarity threshold; if there is only one target vector, the target user's identity is confirmed to be legitimate and the security authentication is passed; if there is no target vector, the target user's security authentication request is rejected; if there are multiple target vectors, the target user's security authentication request is rejected, and an exception message is generated to prompt relevant personnel.

[0047] The iris feature database is a collection that stores a large number of iris feature vectors of registered users, such as the iris feature database of corporate employees used in the employee attendance system, or the iris feature database of financial institution customers used to ensure transaction security.

[0048] Specifically, the similarity between the iris feature vector and each feature vector in the iris feature database is calculated, and it is verified whether there is a target vector in the iris feature database whose similarity is greater than a preset similarity threshold. If there is only one target vector, it means that the iris feature vector is highly similar to a vector in the database, exceeding the preset threshold, thereby confirming that the identity of the target user is legitimate and passing the security authentication. For example, in the access control system, the user is allowed to enter only when the similarity reaches more than 90%. If there is no target vector, it means that a feature vector that is sufficiently similar to it cannot be found in the database, and the target user's security authentication request is rejected. If there are multiple target vectors, this situation may indicate that the system is abnormal or there is a potential security risk, so the target user's security authentication request is rejected, and abnormal information is generated to prompt relevant personnel. For example, an email or text message reminder is sent to the system administrator for timely investigation and processing.

[0049] It should be noted that in this embodiment, the calculation of the similarity is usually based on a certain mathematical model or algorithm, such as Euclidean distance, cosine similarity, etc., which can be set by relevant personnel based on the actual implementation scenario according to requirements such as calculation accuracy, and this embodiment does not impose any restrictions on this.

[0050] The technical solution of the embodiment of the present invention first responds to the security authentication request of the target user, collects a sample picture set of the target user through an image acquisition device, then segments each sample picture in the sample picture set through a masking technology algorithm to obtain each iris template that matches each sample picture, then processes each iris template based on a preset feature fusion algorithm to obtain an iris feature vector that matches the target user, finally searches a pre-established iris feature database for a target vector that matches the iris feature vector, and performs security authentication on the target user based on the matching result, thereby realizing secure identification of the target user based on the iris, reducing the cost of security authentication operations while improving the accuracy of security authentication results, thereby improving the security of the system.

[0051] Embodiment 2

[0052] Figure 2 A flowchart of a security authentication method based on iris recognition is provided in the second embodiment of the present invention. This embodiment is refined based on the above embodiment. In this embodiment, the method of processing each iris template based on a preset feature fusion algorithm to obtain an iris feature vector matching the target user is specifically refined.

[0053] like Figure 2 As shown, the method includes:

[0054] S210 . In response to a security authentication request of a target user, a sample picture set of the target user is collected by an image collection device.

[0055] The sample picture set includes two pictures of the target user including left-eye images and two pictures including right-eye images.

[0056] S220 , performing segmentation processing on each sample image in the sample image set by using a masking technology algorithm to obtain each iris template that matches each sample image.

[0057] S230 , processing each iris template by a difference mean algorithm to obtain a difference mean feature of each iris template, and processing each iris template by a multi-algorithm mean algorithm to obtain an algorithm mean feature of each iris template.

[0058] Among them, the difference mean algorithm is a method of calculating the difference between adjacent pixels or pixel values ​​in a specific area and averaging these differences. For example, when processing an 8x8 pixel area, the difference between adjacent pixels is first calculated, and then these differences are summed and divided by the number of differences. The result is the difference mean feature. This algorithm can effectively capture subtle changes and local features in the iris template; further, the multi-algorithm mean algorithm is a strategy that uses a variety of different calculation methods to obtain mean features. For example, it may be possible to combine multiple methods such as the median algorithm and the weighted average algorithm to process different parts or different attributes of the iris template, and comprehensively average the multiple results obtained. Taking an iris template area containing 100 pixels as an example, the median algorithm is first used to obtain the middle value, and then the weighted average algorithm is used to calculate the average value according to the importance of the pixels. Finally, the two results are averaged again to obtain the multi-algorithm mean feature.

[0059] S240: Concatenate the difference mean features and the algorithm mean features of each iris template based on a preset concatenation rule to obtain target key features that match each iris template.

[0060] Among them, the preset series connection rule can be specifically to connect the difference mean feature in series to the algorithm mean feature, or to connect the algorithm mean feature in series to the difference mean feature; it should be noted that, during any complete implementation of the method described in this embodiment, the series connection rule remains unchanged to ensure that the composition of the target key features is consistent.

[0061] S250: Process each target key feature through a preset feature fusion algorithm to obtain an iris feature vector that matches the target user.

[0062] Among them, each target key feature is processed by a preset feature fusion algorithm to obtain an iris feature vector matching the target user, including: combining each target key feature based on a preset matrix building rule to obtain a target feature matrix; calculating the covariance matrix of the target feature matrix, and performing eigenvalue decomposition on the covariance matrix to obtain a target feature vector matching the target feature matrix; calculating the projection of the target feature matrix in the direction of the target feature vector to obtain an iris feature vector matching the target user.

[0063] Among them, the matrix building rule can be arranged and combined according to the importance, category or other specific logical order of the features. For example, the features related to iris texture are first placed in the upper half of the matrix, and the features related to iris color are placed in the lower half of the matrix; further, the covariance matrix of the target feature matrix is ​​calculated, and the eigenvalue decomposition of the covariance matrix is ​​performed to obtain a target feature vector matching the target feature matrix. The covariance matrix is ​​used to describe the overall variation between multiple variables. By calculating it, it can reflect the correlation between the elements in the target feature matrix. The eigenvalue decomposition is a mathematical method for decomposing a matrix into the form of eigenvalues ​​and eigenvectors, thereby extracting the main feature information of the matrix. Finally, the projection of the target feature matrix in the direction of the target feature vector is calculated to obtain an iris feature vector matching the target user. This projection process can be understood as compressing and mapping the target feature matrix along the direction of the target feature vector, thereby obtaining a vector that can accurately represent the iris features of the target user.

[0064] S260: Search in a pre-established iris feature database whether there is a target vector that matches the iris feature vector, and perform security authentication on the target user according to the matching result.

[0065] The technical solution of the embodiment of the present invention first responds to the security authentication request of the target user, collects the sample picture set of the target user through the image acquisition device, then segments each sample picture in the sample picture set through the masking technology algorithm to obtain each iris template matching each sample picture, then processes each iris template through the difference mean algorithm to obtain the difference mean feature of each iris template, and processes each iris template through the multi-algorithm mean algorithm to obtain the algorithm mean feature of each iris template, then concatenates the difference mean feature and the algorithm mean feature of each iris template based on a preset concatenation rule to obtain the target key feature matching each iris template, and processes each target key feature through a preset feature fusion algorithm to obtain the iris feature vector matching the target user, finally searches in a pre-established iris feature database whether there is a target vector matching the iris feature vector, and performs security authentication on the target user according to the matching result, thereby realizing the security identification of the target user based on the iris, reducing the cost of security authentication operation and improving the accuracy of the security authentication result, thereby improving the security of the system.

[0066] Embodiment 3

[0067] Figure 3 This is a schematic diagram of the structure of a security authentication device based on iris recognition provided in Embodiment 3 of the present invention.

[0068] like Figure 3 As shown, the device comprises:

[0069] The sample collection module 310 is used to collect a sample picture set of the target user through an image collection device in response to a security authentication request of the target user, wherein the sample picture set includes two pictures containing left-eye images and two pictures containing right-eye images of the target user;

[0070] The image segmentation module 320 is used to segment each sample image in the sample image set by using a masking technology algorithm to obtain iris templates that match each sample image.

[0071] A feature fusion module 330 is used to process each iris template based on a preset feature fusion algorithm to obtain an iris feature vector that matches the target user;

[0072] The security authentication module 340 is used to search in a pre-established iris feature database whether there is a target vector that matches the iris feature vector, and to perform security authentication on the target user based on the matching result.

[0073] The technical solution of the embodiment of the present invention first responds to the security authentication request of the target user, collects a sample picture set of the target user through an image acquisition device, then segments each sample picture in the sample picture set through a masking technology algorithm to obtain each iris template that matches each sample picture, then processes each iris template based on a preset feature fusion algorithm to obtain an iris feature vector that matches the target user, finally searches a pre-established iris feature database for a target vector that matches the iris feature vector, and performs security authentication on the target user based on the matching result, thereby realizing secure identification of the target user based on the iris, reducing the cost of security authentication operations while improving the accuracy of security authentication results, thereby improving the security of the system.

[0074] Based on the above embodiment, the picture segmentation module 320 includes:

[0075] A sample picture processing unit, used for performing grayscale processing and smoothing filtering processing on each sample picture in the sample picture set to obtain each processed sample picture;

[0076] The iris template acquisition unit is used to process each processed sample image by using a pre-configured image processing algorithm to obtain an iris template that matches each sample image.

[0077] Based on the above embodiment, the iris template acquisition unit further includes:

[0078] An edge detection unit, used to perform edge detection on each sample image based on an edge detection algorithm to obtain iris edge data that matches each sample image;

[0079] A mask processing unit, used to perform mask processing on each sample image according to each iris edge data using a preset masking algorithm to obtain each masked iris image;

[0080] The threshold segmentation unit is used to segment each masked iris image using a threshold segmentation method to obtain each iris template that matches each sample image.

[0081] Based on the above embodiment, the feature fusion module 330 includes:

[0082] An algorithm mean feature acquisition unit, used to process each iris template by a difference mean algorithm to obtain a difference mean feature of each iris template, and to process each iris template by a multi-algorithm mean algorithm to obtain an algorithm mean feature of each iris template;

[0083] A feature series connection unit is used to connect the difference mean features and the algorithm mean features of each iris template in series based on a preset series connection rule to obtain target key features that match each iris template respectively;

[0084] The iris feature vector acquisition unit is used to process each target key feature through a preset feature fusion algorithm to obtain an iris feature vector matching the target user.

[0085] Based on the above embodiment, the iris feature vector acquisition unit includes:

[0086] A matrix acquisition unit, used to combine each target key feature based on a preset matrix building rule to obtain a target feature matrix;

[0087] A covariance calculation unit, used for calculating the covariance matrix of the target feature matrix, and performing eigenvalue decomposition on the covariance matrix to obtain a target feature vector matching the target feature matrix;

[0088] The projection unit is used to calculate the projection of the target feature matrix in the direction of the target feature vector to obtain an iris feature vector matching the target user.

[0089] Based on the above embodiment, the security authentication module 340 includes:

[0090] A similarity calculation unit, used to calculate the similarity between the iris feature vector and each feature vector in the iris feature database, and to verify whether there is a target vector in the iris feature database whose similarity is greater than a preset similarity threshold;

[0091] A first authentication unit, configured to confirm that the identity of the target user is legitimate and pass the security authentication if there is only one target vector;

[0092] A second authentication unit, configured to reject a security authentication request of a target user if any target vector does not exist;

[0093] The third authentication unit is used to reject the security authentication request of the target user if there are multiple target vectors, and generate abnormal information to prompt relevant personnel.

[0094] The iris recognition-based security authentication device provided in the embodiment of the present invention can execute the iris recognition-based security authentication method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0095] Embodiment 4

[0096] Figure 4A schematic diagram of the structure of an electronic device 10 that can be used to implement an embodiment of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or required herein.

[0097] like Figure 4 As shown, the electronic device 10 includes at least one processor 11, and a memory connected to the at least one processor 11, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 to the random access memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 can also be stored. The processor 11, ROM 12 and RAM 13 are connected to each other through a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0098] A number of components in the electronic device 10 are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0099] The processor 11 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 11 executes the various methods and processes described above, such as a security authentication method based on iris recognition.

[0100] Accordingly, the method comprises:

[0101] In response to a security authentication request of a target user, collecting a sample picture set of the target user through an image acquisition device, wherein the sample picture set includes two pictures of the target user including left-eye images and two pictures including right-eye images;

[0102] Segmenting each sample image in the sample image set by using a masking technology algorithm to obtain iris templates that match each sample image;

[0103] Processing each iris template based on a preset feature fusion algorithm to obtain an iris feature vector matching the target user;

[0104] A search is performed in a pre-established iris feature database to determine whether there is a target vector that matches the iris feature vector, and security authentication is performed on the target user based on the matching result.

[0105] In some embodiments, a security authentication method based on iris recognition may be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the security authentication method based on iris recognition described above may be performed. Alternatively, in other embodiments, the processor 11 may be configured to execute a security authentication method based on iris recognition in any other appropriate manner (e.g., by means of firmware).

[0106] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0107] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that when the computer program is executed by the processor, the functions / operations specified in the flow chart and / or block diagram are implemented. The computer program may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0108] In the context of the present invention, a computer-readable storage medium may be a tangible medium that may contain or store a computer program for use by or in combination with an instruction execution system, device or equipment. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, 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 foregoing.

[0109] To provide interaction with a user, the systems and techniques described herein may be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).

[0110] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0111] A computing system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The client and server relationship is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services.

[0112] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of the present invention can be achieved, and this document does not limit this.

Claims

1. A security authentication method based on iris recognition, characterized in that: include: In response to a security authentication request of a target user, a sample picture set of the target user is collected by an image collection device, wherein the sample picture set includes two pictures of the target user including left-eye images and two pictures including right-eye images; Segmenting each sample image in the sample image set by using a masking technology algorithm to obtain iris templates that match each sample image; Processing each iris template based on a preset feature fusion algorithm to obtain an iris feature vector matching the target user; A search is performed in a pre-established iris feature database to determine whether there is a target vector that matches the iris feature vector, and security authentication is performed on the target user based on the matching result.

2. The method according to claim 1, characterized in that The sample images in the sample image set are segmented by a masking technology algorithm to obtain iris templates that match the sample images, including: Performing grayscale processing and smoothing filtering processing on each sample image in the sample image set to obtain each processed sample image; The processed sample images are processed respectively by a pre-configured image processing algorithm to obtain iris templates that match the sample images respectively.

3. The method according to claim 2, characterized in that The processed sample images are processed respectively by a pre-configured image processing algorithm to obtain iris templates that match the sample images respectively, including: Perform edge detection on each sample image based on an edge detection algorithm to obtain iris edge data that matches each sample image; According to each iris edge data, each sample image is masked using a preset masking algorithm to obtain each masked iris image; The threshold segmentation method is used to segment each masked iris image to obtain each iris template that matches each sample image.

4. The method according to claim 1, characterized in that: Each iris template is processed based on a preset feature fusion algorithm to obtain an iris feature vector matching the target user, including: Each iris template is processed by a difference mean algorithm to obtain a difference mean feature of each iris template, and each iris template is processed by a multi-algorithm mean algorithm to obtain an algorithm mean feature of each iris template; The difference mean features and the algorithm mean features of each iris template are connected in series based on a preset series rule to obtain target key features that match each iris template respectively; Each target key feature is processed by a preset feature fusion algorithm to obtain an iris feature vector that matches the target user.

5. The method according to claim 4, characterized in that Each target key feature is processed by a preset feature fusion algorithm to obtain an iris feature vector matching the target user, including: Combine the key features of each target based on the preset matrix building rules to obtain the target feature matrix; Calculating a covariance matrix of the target feature matrix, and performing eigenvalue decomposition on the covariance matrix to obtain a target feature vector that matches the target feature matrix; The projection of the target feature matrix in the direction of the target feature vector is calculated to obtain an iris feature vector matching the target user.

6. The method according to claim 1, characterized in that Searching in a pre-established iris feature database whether there is a target vector matching the iris feature vector, and performing security authentication on the target user according to the matching result, including: Calculating the similarity between the iris feature vector and each feature vector in the iris feature database, and verifying whether there is a target vector in the iris feature database whose similarity is greater than a preset similarity threshold; If there is only one target vector, the target user's identity is confirmed to be legitimate and the security authentication is passed; If any target vector does not exist, the target user's security authentication request is rejected; If there are multiple target vectors, the target user's security authentication request will be rejected, and an exception message will be generated to prompt relevant personnel.

7. A security authentication device based on iris recognition, characterized in that: include: A sample collection module, configured to collect a sample picture set of the target user through an image collection device in response to a security authentication request of the target user, wherein the sample picture set includes two pictures of the target user including a left eye image and two pictures including a right eye image; An image segmentation module is used to segment each sample image in the sample image set by using a masking technology algorithm to obtain iris templates that match each sample image; A feature fusion module, used to process each iris template based on a preset feature fusion algorithm to obtain an iris feature vector matching the target user; The security authentication module is used to search in a pre-established iris feature database whether there is a target vector that matches the iris feature vector, and to perform security authentication on the target user according to the matching result.

8. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute a security authentication method based on iris recognition as described in any one of claims 1-6.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement a security authentication method based on iris recognition according to any one of claims 1 to 6 when executed.

10. A computer program product, characterized in that The computer program product comprises a computer program, and when the computer program is executed by a processor, the computer program implements a security authentication method based on iris recognition according to any one of claims 1 to 6.

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