Multi-lens iris recognition module and recognition method

Abstract

The invention relates to the technical field of identity authentication, in particular to a multi-lens iris recognition module and method, and the module comprises a lens adjustment unit, an image capture unit, an image quality evaluation unit, a color correction unit, a detail optimization unit and an identity authentication unit. According to the invention, the iris images with different depths of field are captured and the iris acquisition distance is enlarged by differentiating the aperture size and the focusing distance of the lens, so that the distance change of a user is effectively adapted, the recognition accuracy and the user experience are improved, and the high-quality iris images are screened through multi-parameter quality evaluation, so that the recognition precision is improved, and the user experience is improved. The method has the advantages that the image recognition accuracy is improved by enhancing the iris edge, the iris recognition efficiency and accuracy are optimized, the influence of environment change and individual difference on the recognition effect is reduced, and the recognition efficiency is improved. And a safer and more reliable identity verification scheme is provided for the user.

Description

Technical Field

[0001] The present invention relates to the technical field of identity authentication, and in particular to a multi-lens iris recognition module and a recognition method. Background Art

[0002] The field of identity verification technology aims to ensure that only authorized individuals can access specific resources or information. The technology covers a wide range of technologies from traditional password authentication to biometric authentication, including fingerprint, face, voice and iris recognition. Iris recognition technology is particularly important in high-security environments due to its high accuracy and difficult-to-forge characteristics. This technology uses image recognition and pattern matching algorithms to analyze the complex texture of the iris of the eye to achieve fast and reliable user identity verification.

[0003] Among them, the multi-lens iris recognition module is an identity authentication unit that uses multiple camera lenses to capture iris images to enhance recognition accuracy and flexibility. The module is particularly suitable for occasions that require high security measures, such as airport security, banking systems, and entrances to government facilities. The multi-lens can quickly and accurately capture high-quality iris images while the user is moving, and maintain a high recognition rate even in low light or with slight movement of the user's head. The multi-lens configuration can reduce the impact of environmental factors on the recognition effect and provide a more reliable security verification solution.

[0004] The single lens of the traditional recognition module will face the problem of reduced recognition rate due to poor lighting conditions or user head movement. It is easily limited by light intensity and direction, resulting in insufficient contrast and clarity when capturing images, affecting the final authentication accuracy. Traditional modules lack flexibility in dealing with differences in user height and position changes, and often require users to fine-tune their body position during use, which not only reduces the user experience but also increases the complexity of operation. In situations where multiple users pass quickly, such as airport security checks, this deficiency can lead to congestion and inefficient processing. Therefore, the existing technology shows obvious limitations in meeting the needs of high-throughput and high-precision recognition. Especially in application scenarios with high security requirements, these deficiencies can lead to safety hazards and recognition errors. Summary of the invention

[0005] The purpose of the present invention is to solve the shortcomings of the prior art and to propose a multi-lens iris recognition module and a recognition method.

[0006] In order to achieve the above object, the present invention adopts the following technical solution: a multi-lens iris recognition module, the module comprising:

[0007] The lens adjustment unit monitors the current ambient light intensity based on the image acquisition environment, compares it with the preset light standard, adjusts the ISO and exposure time of each image capture lens, and adjusts the aperture size and focus distance of each image lens to obtain the adjusted shooting parameters;

[0008] The image capturing unit analyzes the user image based on the adjusted shooting parameters, determines the user's height, dynamically adjusts the angle of the image capturing lens, and simultaneously captures the user's iris image through multiple image capturing lenses to obtain an iris image set;

[0009] The image quality assessment unit performs multi-parameter quality assessment on the iris image based on the iris image set, selects an iris image of target quality, and obtains an iris image screening result;

[0010] The color correction unit analyzes the color distribution data in the image based on the iris image screening result, compares the color distribution data with the standard iris color parameter set, corrects the color deviation in the image, and obtains a color-corrected iris image;

[0011] The detail optimization unit identifies the iris edge in the iris image through image analysis based on the color-corrected iris image, adjusts the contrast of the iris edge area in the image, and obtains a detail-optimized iris image by supplementing the detail loss area in the image;

[0012] The identity authentication unit optimizes the iris image based on the details, matches it with the iris data pre-stored in the database, and performs identity matching by dynamically adjusting the matching degree threshold to obtain an identity authentication result.

[0013] As a further solution of the present invention, the adjusted shooting parameters include ISO sensitivity, exposure time and aperture parameters, the iris image set includes an iris image set with multiple depths of field and multi-angle viewing angle images, the iris image screening result is specifically an image of target clarity, noise amount and contrast, the color-corrected iris image is specifically an image that has undergone color balance adjustment, chromatic aberration correction and color consistency, the detail-optimized iris image is specifically an image with improved edge clarity, enhanced local details and repaired areas of uneven lighting, and the identity authentication result includes a matching score, a successful matching mark and identity information.

[0014] As a further solution of the present invention, the lens adjustment unit includes:

[0015] Based on the image acquisition environment, the light detection subunit monitors the current ambient light intensity through a light sensor, compares it with the preset light standard, analyzes the light condition deviation, and obtains the ambient light data;

[0016] The photosensitivity adjustment subunit adjusts the ISO sensitivity of each image capture lens based on the ambient light data, and adjusts the exposure time to match the current light intensity, thereby obtaining photosensitivity adjustment parameters;

[0017] The depth of field adjustment subunit adjusts the aperture and focal length of each image capture lens based on the photosensitivity adjustment parameters and according to the differentiated depth of field iris image capture target, adjusts the focal distance, optimizes the focusing effect of the lens on the differentiated distance, and obtains the adjusted shooting parameters.

[0018] As a further solution of the present invention, the image capturing unit comprises:

[0019] The height analysis subunit captures the user image based on the adjusted shooting parameters, and calculates the user's height by analyzing the proportions and key body markers in the image to obtain the user's height data;

[0020] The angle adjustment subunit dynamically adjusts the angle of the image capture lens based on the user height data, and optimizes the image capture position of each lens by adjusting the lens angle to match the user's eye height, thereby obtaining angle adjustment data;

[0021] The iris capture subunit controls the lens to simultaneously capture images of the user's irises based on the angle adjustment data and utilizes a synchronous trigger mechanism, and captures iris images with differentiated depths of field in real time to obtain an iris image set.

[0022] As a further solution of the present invention, the image quality assessment unit includes:

[0023] The image parameter extraction subunit analyzes the iris image based on the iris image set and extracts the image clarity, contrast and noise indexes through image processing technology to obtain the basic parameters of the iris image;

[0024] The quality analysis subunit calculates the quality index of the iris image based on the basic parameters of the iris image, by considering the clarity, contrast and noise index, and according to the preset weights to obtain the iris image quality score;

[0025] The scoring and screening subunit sorts the images based on the iris image quality scores, screens out iris images that meet a predetermined quality standard, and obtains iris image screening results.

[0026] As a further solution of the present invention, the formula for calculating the quality index of the iris image is:

[0027]

[0028] Among them, C represents the contrast value of the iris image, C max represents the maximum contrast value, S represents the clarity value of the iris image, and Smax represents the maximum clarity value, N represents the noise level of the iris image, and N max Represents the maximum noise level, W c , W s and W n Represent the weight coefficients of contrast, clarity and noise index respectively.

[0029] As a further solution of the present invention, the color correction unit includes:

[0030] The color distribution analysis subunit performs spectrum analysis on the color of the iris image based on the iris image screening result, analyzes the color distribution data in the image, compares it with the preset standard iris color parameters, identifies the color deviation, and obtains the color analysis data;

[0031] The color balance adjustment subunit performs color balance adjustment on the red, green and blue channels in the image based on the color analysis data, and optimizes the color performance of the image by adjusting the color balance and matching the standard iris color parameter set to obtain a color balance adjustment result;

[0032] The color difference correction subunit corrects the color in the image based on the color balance adjustment result, optimizes the color authenticity and consistency of the image by adjusting the hue, saturation and brightness, and obtains a color-corrected iris image.

[0033] As a further solution of the present invention, the detail optimization unit includes:

[0034] The edge detection subunit analyzes the iris image through edge detection based on the color-corrected iris image, identifies the shape and position of the iris edge in the image, and obtains an edge feature map;

[0035] The contrast enhancement subunit adjusts the contrast of the iris edge area based on the edge feature map to highlight the iris boundary in the image, thereby obtaining an edge enhanced iris image;

[0036] The detail restoration subunit analyzes the detail loss area in the iris image caused by uneven illumination and camera distortion based on the edge-enhanced iris image, repairs the detail loss area, and obtains a detail-optimized iris image.

[0037] As a further solution of the present invention, the identity verification unit includes:

[0038] The image partition matching subunit optimizes the iris image based on the details, performs partition processing on the iris image, decomposes the iris image into multiple regions, and obtains partition matching data;

[0039] The matching evaluation subunit compares each partition with the iris data pre-stored in the database based on the partition matching data, evaluates the matching degree of each partition, and obtains a partition matching evaluation result;

[0040] The matching result confirmation subunit performs identity authentication judgment based on the partition matching evaluation result by analyzing the matching degree of each partition, verifies whether it matches the pre-stored data in the database, and obtains the identity authentication result.

[0041] A multi-lens iris recognition method is implemented based on the multi-lens iris recognition module, and comprises the following steps:

[0042] S1: Based on the image acquisition environment, adjust the ISO and exposure time of each image capture lens, and adjust the aperture size and focus distance of each image lens to obtain adjusted shooting parameters;

[0043] S2: Based on the adjusted shooting parameters, the user's image is analyzed to determine the user's height, the angle of the image capture lens is dynamically adjusted, and the user's iris image is captured simultaneously through multiple image capture lenses to obtain an iris image set;

[0044] S3: Based on the iris image set, perform multi-parameter quality assessment on the iris image, select iris images of target quality, and obtain iris image screening results;

[0045] S4: Based on the iris image screening result, by adjusting the color balance of the red, green and blue channels, correcting the color deviation in the image, adjusting the contrast of the iris edge area in the image, and supplementing the detail loss area in the image, a detail-optimized iris image is obtained;

[0046] S5: Optimize the iris image based on the details, match it with the iris data pre-stored in the database, and perform identity matching by dynamically adjusting the matching threshold to obtain an identity authentication result.

[0047] Compared with the prior art, the advantages and positive effects of the present invention are:

[0048] In the present invention, by differentiating the aperture size and focusing distance of the lens, iris images of different depths of field are captured, the iris collection distance is expanded, and the user distance change is effectively adapted to improve recognition accuracy and user experience. Multi-parameter quality evaluation is used to screen high-quality iris images, thereby improving recognition accuracy and reducing the complexity of data processing. By strengthening the iris edge, the recognition accuracy of the image is improved, ensuring reliable identity authentication in a high-security environment, optimizing the efficiency and accuracy of iris recognition, reducing the impact of environmental changes and individual differences on the recognition effect, and providing users with a more secure and reliable identity authentication solution. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 It is a module flow chart of the present invention;

[0050] Figure 2 It is a schematic diagram of the module framework of the present invention;

[0051] Figure 3 is a flow chart of the lens adjustment unit of the present invention;

[0052] Figure 4 is a flow chart of an image capturing unit of the present invention;

[0053] Figure 5 is a flow chart of an image quality assessment unit of the present invention;

[0054] Figure 6 is a flow chart of a color correction unit of the present invention;

[0055] Figure 7 A flowchart of the detail optimization unit of the present invention;

[0056] Figure 8 is a flow chart of the identity authentication unit of the present invention;

[0057] Fig. 9 It is a schematic diagram of the method steps of the present invention. DETAILED DESCRIPTION

[0058] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0059] In the description of the present invention, it should be understood that the terms "length", "width", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside" and the like indicate positions or positional relationships based on the positions or positional relationships shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, in the description of the present invention, "multiple" means two or more, unless otherwise clearly and specifically defined.

[0060] See also Figure 1 The present invention provides a technical solution: a multi-lens iris recognition module, the module comprising:

[0061] The lens adjustment unit monitors the current ambient light intensity through a light sensor based on the image acquisition environment, compares it with the preset light standard, adjusts the ISO and exposure time of each image capture lens, and adjusts the aperture size and focus distance of each image lens to focus each lens at a differentiated depth of field, and obtains the adjusted shooting parameters;

[0062] The image capturing unit determines the height of the user by analyzing the user image based on the adjusted shooting parameters, dynamically adjusts the angle of the image capturing lens according to the user height data, optimizes the image capturing position, and simultaneously captures the user's iris image through multiple image capturing lenses to obtain an iris image set;

[0063] The image quality assessment unit performs multi-parameter quality assessment on the iris image based on the iris image set, analyzes the clarity, contrast and noise level of the image, selects the iris image of target quality by assessing the quality of the iris image, and obtains the iris image screening result;

[0064] The color correction unit analyzes the color spectrum in the iris image and the color distribution data in the image based on the iris image screening result, and compares the color spectrum with the standard iris color parameter set, and adjusts the color balance of the red, green and blue channels to correct the color deviation in the image, thereby obtaining a color-corrected iris image;

[0065] The detail optimization unit identifies the iris edge in the iris image through image analysis based on the color-corrected iris image, adjusts the contrast of the iris edge area in the image through contrast enhancement, and restores the detail loss caused by uneven lighting and camera distortion by supplementing the detail loss area in the image, thereby obtaining a detail-optimized iris image;

[0066] The identity authentication unit optimizes the iris image based on the details, matches it with the iris data pre-stored in the database, and performs identity matching by dynamically adjusting the matching threshold to obtain the identity authentication result.

[0067] The adjusted shooting parameters include ISO sensitivity, exposure time and aperture parameters. The iris image set includes iris image sets with multiple depths of field and multi-angle viewing angle images. The iris image screening results are specifically images of target clarity, noise amount and contrast. The color-corrected iris image is specifically an image that has undergone color balance adjustment, chromatic aberration correction and color consistency. The detail-optimized iris image is specifically an image with improved edge clarity, enhanced local details and repaired areas of uneven lighting. The identity authentication results include matching scores, successful matching marks and identity information.

[0068] See also Figure 2 and Figure 3 , the lens adjustment unit includes an illumination detection subunit, a photosensitivity adjustment subunit, and a depth of field adjustment subunit;

[0069] Based on the image acquisition environment, the light detection subunit monitors the current ambient light intensity through a light sensor, compares it with the preset light standard, analyzes the light condition deviation, and obtains the ambient light data;

[0070] The light detection subunit deploys multiple light sensors according to the image acquisition environment. The sensors can capture and record the light intensity in the environment in real time. The light sensor is set to sample at a frequency of one second per second to collect light intensity data, and the data forms a real-time light intensity record. The recorded light data is analyzed in real time, and the deviation of the light conditions in the current environment is calculated by comparing the actual light data with the light standard preset by the system. For example, if the system preset standard is 500lx and the current measured value is 450lx, the deviation is -50lx. This data directly reflects the insufficient light intensity. The ambient light data is obtained by continuous data collection and analysis.

[0071] The sensitivity adjustment subunit adjusts the ISO sensitivity of each image capture lens based on the ambient light data, and adjusts the exposure time to match the current light intensity to obtain the sensitivity adjustment parameters;

[0072] The sensitivity adjustment subunit adjusts the sensitivity of each lens in the image capture device based on the ambient light data. Set the appropriate ISO sensitivity for each lens. If the ambient light data shows that the light intensity is lower than the standard, increase the ISO value to enhance the sensitivity. Adjust the exposure time of the lens through the software control interface to match the current lighting conditions. For example, if the light is dim, the exposure time may be adjusted from 1 / 100 second to 1 / 50 second. The feedback mechanism continuously compares the ambient light intensity with the image quality, and gradually refines the adjustment until the best sensitivity and exposure combination is found to obtain the sensitivity adjustment parameters.

[0073] The depth of field adjustment subunit adjusts the aperture and focal length of each image capture lens based on the photosensitivity adjustment parameters and the differentiated depth of field iris image capture target, adjusts the focal distance, optimizes the focusing effect of the lens on the differentiated distance, and obtains the adjusted shooting parameters.

[0074] The depth of field adjustment subunit sets the aperture and focal length of the image capture lens based on the photosensitivity adjustment parameters. According to the capture target, the aperture size and focal length of each lens are adjusted to adapt to different focusing requirements from near view to far view. According to the actual distance between the capture target and the lens, the required aperture and focal length values ​​are calculated. For example, for close-range targets, the aperture is reduced and the focal length is shortened to enhance the focusing accuracy and depth of field effect. The program optimizes the focusing effect of each lens on targets at different distances through precise distance sensing and parameter adjustment, and obtains the adjusted shooting parameters.

[0075] See also Figure 2 and Figure 4 ,The image capturing unit includes a height analyzing subunit, an angle adjusting subunit, and an iris capturing subunit;

[0076] The height analysis subunit captures the user image based on the adjusted shooting parameters, and calculates the user's height by analyzing the proportions and key body landmarks in the image to obtain the user's height data;

[0077] Based on the adjusted shooting parameters, the height analysis subunit captures the user's full-body image and uses image analysis technology to distinguish the proportions and key body markers in the image, such as the top of the head and the soles of the feet. By measuring the proportional relationship between the markers and combining known shooting parameters (such as camera distance and angle), the user's height is analyzed. The accuracy and reliability of the captured height data are ensured through geometric transformation and scale analysis of the image, and the user's height data is obtained.

[0078] The angle adjustment subunit dynamically adjusts the angle of the image capture lens based on the user's height data, and optimizes the image capture position of each lens by adjusting the lens angle to match the user's eye height, thereby obtaining angle adjustment data;

[0079] The angle adjustment subunit is based on the user's height data and the height at which the lens is installed. It analyzes the height difference between the lens and the user's glasses, and dynamically adjusts the tilt angle of the lens based on the height difference to ensure that the center line of the lens matches the user's eyes. The ideal lens angle is calculated based on the user's height data, and the physical position of the camera is adjusted through the motor control system so that the camera can capture the user's eyes and facial expressions at the best angle. The image quality is continuously monitored during the adjustment process to ensure the optimization of the image capture position and obtain angle adjustment data.

[0080] The iris capture subunit adjusts the angle data and uses a synchronous trigger mechanism to control the lens to simultaneously capture images of the user's irises, capturing iris images with differentiated depths of field in real time to obtain an iris image set.

[0081] The iris capture subunit starts the synchronization trigger mechanism based on the angle adjustment data, so that all configured cameras can accurately capture the user's iris image at the same time, enhancing the time synchronization and capture efficiency of the image, and obtaining the iris image set by real-time processing and analysis of the image.

[0082] See also Figure 2 and Figure 5 ,The image quality assessment unit includes an image parameter extraction subunit, a quality analysis subunit, and a score screening subunit.

Claims

1. A multi-lens iris recognition module, characterized in that: The modules include: The lens adjustment unit monitors the current ambient light intensity based on the image acquisition environment, compares it with the preset light standard, adjusts the ISO and exposure time of each image capture lens, and adjusts the aperture size and focus distance of each image lens to obtain the adjusted shooting parameters; The image capturing unit analyzes the user image based on the adjusted shooting parameters, determines the user's height, dynamically adjusts the angle of the image capturing lens, and simultaneously captures the user's iris image through multiple image capturing lenses to obtain an iris image set; The image quality assessment unit performs multi-parameter quality assessment on the iris image based on the iris image set, selects an iris image of target quality, and obtains an iris image screening result; The color correction unit analyzes the color distribution data in the image based on the iris image screening result, compares the color distribution data with the standard iris color parameter set, corrects the color deviation in the image, and obtains a color-corrected iris image; The detail optimization unit identifies the iris edge in the iris image through image analysis based on the color-corrected iris image, adjusts the contrast of the iris edge area in the image, and obtains a detail-optimized iris image by supplementing the detail loss area in the image; The identity authentication unit optimizes the iris image based on the details, matches it with the iris data pre-stored in the database, and performs identity matching by dynamically adjusting the matching degree threshold to obtain an identity authentication result.

2. The multi-lens iris recognition module according to claim 1, characterized in that: The adjusted shooting parameters include ISO sensitivity, exposure time and aperture parameters, the iris image set includes iris image sets with multiple depths of field and multi-angle viewing angle images, the iris image screening results are specifically images of target clarity, noise volume and contrast, the color-corrected iris image is specifically an image that has undergone color balance adjustment, chromatic aberration correction and color consistency, the detail-optimized iris image is specifically an image with improved edge clarity, enhanced local details and repaired areas of uneven lighting, and the identity authentication result includes a matching score, a successful matching mark and identity information.

3. The multi-lens iris recognition module according to claim 1, characterized in that: The lens adjustment unit comprises: Based on the image acquisition environment, the light detection subunit monitors the current ambient light intensity through a light sensor, compares it with the preset light standard, analyzes the light condition deviation, and obtains the ambient light data; The photosensitivity adjustment subunit adjusts the ISO sensitivity of each image capture lens based on the ambient light data, and adjusts the exposure time to match the current light intensity, thereby obtaining photosensitivity adjustment parameters; The depth of field adjustment subunit adjusts the aperture and focal length of each image capture lens based on the photosensitivity adjustment parameters and according to the differentiated depth of field iris image capture target, adjusts the focal distance, optimizes the focusing effect of the lens on the differentiated distance, and obtains the adjusted shooting parameters.

4. The multi-lens iris recognition module according to claim 1, characterized in that: The image capturing unit comprises: The height analysis subunit captures the user image based on the adjusted shooting parameters, and calculates the user's height by analyzing the proportions and key body markers in the image to obtain the user's height data; The angle adjustment subunit dynamically adjusts the angle of the image capture lens based on the user height data, and optimizes the image capture position of each lens by adjusting the lens angle to match the user's eye height, thereby obtaining angle adjustment data; The iris capture subunit controls the lens to simultaneously capture images of the user's irises based on the angle adjustment data and utilizes a synchronous trigger mechanism, and captures iris images with differentiated depths of field in real time to obtain an iris image set.

5. The multi-lens iris recognition module according to claim 1, characterized in that: The image quality assessment unit comprises: The image parameter extraction subunit analyzes the iris image based on the iris image set and extracts the image clarity, contrast and noise indexes through image processing technology to obtain the basic parameters of the iris image; The quality analysis subunit calculates the quality index of the iris image based on the basic parameters of the iris image, by considering the clarity, contrast and noise index, and according to the preset weights to obtain the iris image quality score; The scoring and screening subunit sorts the images based on the iris image quality scores, screens out iris images that meet a predetermined quality standard, and obtains iris image screening results.

6. The multi-lens iris recognition module according to claim 5, characterized in that: The formula for calculating the quality index of the iris image is: Where C represents the contrast value of the iris image, C max represents the maximum contrast value, S represents the clarity value of the iris image, and S max represents the maximum clarity value, N represents the noise level of the iris image, and N max Represents the maximum noise level, W c , W s and W n Represent the weight coefficients of contrast, clarity and noise index respectively.

7. The multi-lens iris recognition module according to claim 1, characterized in that: The color correction unit comprises: The color distribution analysis subunit performs spectrum analysis on the color of the iris image based on the iris image screening result, analyzes the color distribution data in the image, compares it with the preset standard iris color parameters, identifies the color deviation, and obtains the color analysis data; The color balance adjustment subunit performs color balance adjustment on the red, green and blue channels in the image based on the color analysis data, and optimizes the color performance of the image by adjusting the color balance and matching the standard iris color parameter set to obtain a color balance adjustment result; The color difference correction subunit corrects the color in the image based on the color balance adjustment result, optimizes the color authenticity and consistency of the image by adjusting the hue, saturation and brightness, and obtains a color-corrected iris image.

8. The multi-lens iris recognition module according to claim 1, characterized in that: The detail optimization unit comprises: The edge detection subunit analyzes the iris image through edge detection based on the color-corrected iris image, identifies the shape and position of the iris edge in the image, and obtains an edge feature map; The contrast enhancement subunit adjusts the contrast of the iris edge area based on the edge feature map to highlight the iris boundary in the image, thereby obtaining an edge enhanced iris image; The detail restoration subunit analyzes the detail loss area in the iris image caused by uneven illumination and camera distortion based on the edge-enhanced iris image, repairs the detail loss area, and obtains a detail-optimized iris image.

9. The multi-lens iris recognition module according to claim 1, characterized in that: The identity verification unit comprises: The image partition matching subunit optimizes the iris image based on the details, performs partition processing on the iris image, decomposes the iris image into multiple regions, and obtains partition matching data; The matching evaluation subunit compares each partition with the iris data pre-stored in the database based on the partition matching data, evaluates the matching degree of each partition, and obtains a partition matching evaluation result; The matching result confirmation subunit analyzes the matching degree of each partition based on the partition matching degree evaluation result, performs identity authentication judgment, verifies whether it matches the pre-stored data in the database, and obtains the identity authentication result.

10. A multi-lens iris recognition method, characterized in that: The multi-lens iris recognition module according to any one of claims 1 to 9 is implemented, comprising the following steps: Based on the image acquisition environment, the ISO and exposure time of each image capture lens are adjusted, and the aperture size and focus distance of each image lens are adjusted to obtain adjusted shooting parameters; Based on the adjusted shooting parameters, the user's image is analyzed to determine the user's height, the angle of the image capture lens is dynamically adjusted, and the user's iris image is captured simultaneously through multiple image capture lenses to obtain an iris image set; Based on the iris image set, a multi-parameter quality assessment is performed on the iris image, an iris image of target quality is selected, and an iris image screening result is obtained; Based on the iris image screening result, by adjusting the color balance of the red, green and blue channels, correcting the color deviation in the image, adjusting the contrast of the iris edge area in the image, and supplementing the detail loss area in the image, a detail-optimized iris image is obtained; The iris image is optimized based on the details, matched with the iris data pre-stored in the database, and identity matching is performed by dynamically adjusting the matching degree threshold to obtain an identity authentication result.

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