US-20260127911-A1 - IMAGE PROCESSING METHOD AND APPARATUS, COMPUTER DEVICE, COMPUTER-READABLE STORAGE MEDIUM, AND COMPUTER PROGRAM PRODUCT

Abstract

This application discloses an image processing method performed by a computer device. The method includes: obtaining a first embedded feature of a first image, the first image being a palm print image; recognizing a target image type to which the first image belongs; obtaining an image feature set associated with the target image type, the image feature set including image embedded features of target images of a plurality of objects, each object in an object set having respective object identity information; obtaining a feature matching degree between the first embedded feature and each image embedded feature; and determining, among the plurality of objects, object identity information of an object whose associated image embedded feature has a highest feature matching degree with the first embedded feature for an object to which the first image belongs.

Inventors

• Jun Wang
• Runzeng GUO
• Shaoming WANG
• Jingyun Zhang

Assignees

• TENCENT TECHNOLOGY (SHENZHEN) COMPANY LIMITED

Dates

Publication Date

20260507

Application Date

20260105

Priority Date

20240715

Claims (20)

1. 1 . An image processing method performed by a computer device, the method comprising: obtaining a first embedded feature of a first image, the first image being a palm print image; recognizing a target image type to which the first image belongs; obtaining an image feature set associated with the target image type, the image feature set comprising image embedded features of target images of a plurality of objects, each object having respective object identity information; determining a feature matching degree between the first embedded feature and each image embedded feature in the image feature set; and determining, among the plurality of objects, object identity information of an object whose associated image embedded feature has a highest feature matching degree with the first embedded feature for an object to which the first image belongs.
2. 2 . The method according to claim 1 , wherein the obtaining a first embedded feature of a first image comprises: performing feature extraction on a second image of a palm, to obtain a second embedded feature of the second image; obtaining a reference feature set, the reference feature set comprising reference embedded features of a plurality of reference images, and the reference images being palm print images of the objects in a reference pose; obtaining a feature matching degree between the second embedded feature and each reference embedded feature; and determining the second image as the first image when the feature matching degree between the second embedded feature and each reference embedded feature is less than a first matching degree threshold.
3. 3 . The method according to claim 1 , wherein the method further comprises: determining a first candidate embedded feature from a reference feature set, the feature matching degree between the first candidate embedded feature and the second embedded feature being greater than or equal to the first matching degree threshold; determining an object to which a first candidate embedded feature having a largest feature matching degree with the second embedded feature belongs as a first recognition object; and determining object identity information of the first recognition object as identity recognition information for an object to which the second image belongs.
4. 4 . The method according to claim 1 , wherein the determining, among the plurality of objects, object identity information of an object whose associated image embedded feature has a highest feature matching degree with the first embedded feature for an object to which the first image belongs comprises: obtaining, when the feature matching degree between the first embedded feature and the image embedded feature is less than a second matching degree threshold, target object identification information of the object to which the first image belongs; performing feature extraction on the first image, to generate a third embedded feature of the first image; and determining, based on the target object identification information and the third embedded feature, the identity recognition information for the object to which the first image belongs.
5. 5 . The method according to claim 1 , wherein the method further comprises: determining a second candidate embedded feature from the image feature set, a feature matching degree between the second candidate embedded feature and the first embedded feature being greater than or equal to a second matching degree threshold; determining an object to which a second candidate embedded feature having the highest feature matching degree with the second embedded feature belongs as a second recognition object; and determining the object identity information of the second recognition object as the identity recognition information for the object to which the first image belongs.
6. 6 . The method according to claim 1 , wherein the recognizing a target image type to which the first image belongs comprises: inputting the first image into a trained multi-classification network; and invoking the trained multi-classification network to recognize, from a plurality of set image types, the target image type to which the first image belongs.
7. 7 . The method according to claim 1 , wherein the first image is acquired by the palm print image acquisition device; and the recognizing a target image type to which the first image belongs comprises: obtaining a target angle between an image plane corresponding to the first image and a coordinate system in which the palm print image acquisition device is located; and determining, when the target angle is larger than a set angle threshold, a first image type as the target image type to which the first image belongs.
8. 8 . The method according to claim 1 , wherein the determining a feature matching degree between the first embedded feature and each image embedded feature in the image feature set comprises: determining a cosine similarity between the first embedded feature and each image embedded feature in the image feature set; and determining the cosine similarity between the first embedded feature and the image embedded features as the feature matching degree between the first embedded feature and the image embedded feature.
9. 9 . The method according to claim 1 , wherein the first image is acquired in real time when execution of a target service is triggered; and the method further comprises: obtaining, when the identity recognition information determined for the object to which the first image belongs is object identity information of a target object, a service permission of the target object for the target service; and executing the target service for the target object based on the service permission of the target object for the target service.
10. 10 . A computer device, comprising a memory and a processor, the memory having a computer program stored therein, and the computer program, when executed by the processor, causing the computer device to perform an image processing method including: obtaining a first embedded feature of a first image, the first image being a palm print image; recognizing a target image type to which the first image belongs; obtaining an image feature set associated with the target image type, the image feature set comprising image embedded features of target images of a plurality of objects, each object having respective object identity information; determining a feature matching degree between the first embedded feature and each image embedded feature in the image feature set; and determining, among the plurality of objects, object identity information of an object whose associated image embedded feature has a highest feature matching degree with the first embedded feature for an object to which the first image belongs.
11. 11 . The computer device according to claim 10 , wherein the obtaining a first embedded feature of a first image comprises: performing feature extraction on a second image of a palm, to obtain a second embedded feature of the second image; obtaining a reference feature set, the reference feature set comprising reference embedded features of a plurality of reference images, and the reference images being palm print images of the objects in a reference pose; obtaining a feature matching degree between the second embedded feature and each reference embedded feature; and determining the second image as the first image when the feature matching degree between the second embedded feature and each reference embedded feature is less than a first matching degree threshold.
12. 12 . The computer device according to claim 10 , wherein the method further comprises: determining a first candidate embedded feature from a reference feature set, the feature matching degree between the first candidate embedded feature and the second embedded feature being greater than or equal to the first matching degree threshold; determining an object to which a first candidate embedded feature having a largest feature matching degree with the second embedded feature belongs as a first recognition object; and determining object identity information of the first recognition object as identity recognition information for an object to which the second image belongs.
13. 13 . The computer device according to claim 10 , wherein the determining, among the plurality of objects, object identity information of an object whose associated image embedded feature has a highest feature matching degree with the first embedded feature for an object to which the first image belongs comprises: obtaining, when the feature matching degree between the first embedded feature and the image embedded feature is less than a second matching degree threshold, target object identification information of the object to which the first image belongs; performing feature extraction on the first image, to generate a third embedded feature of the first image; and determining, based on the target object identification information and the third embedded feature, the identity recognition information for the object to which the first image belongs.
14. 14 . The computer device according to claim 10 , wherein the method further comprises: determining a second candidate embedded feature from the image feature set, a feature matching degree between the second candidate embedded feature and the first embedded feature being greater than or equal to a second matching degree threshold; determining an object to which a second candidate embedded feature having the highest feature matching degree with the second embedded feature belongs as a second recognition object; and determining the object identity information of the second recognition object as the identity recognition information for the object to which the first image belongs.
15. 15 . The computer device according to claim 10 , wherein the recognizing a target image type to which the first image belongs comprises: inputting the first image into a trained multi-classification network; and invoking the trained multi-classification network to recognize, from a plurality of set image types, the target image type to which the first image belongs.
16. 16 . The computer device according to claim 10 , wherein the first image is acquired by the palm print image acquisition device; and the recognizing a target image type to which the first image belongs comprises: obtaining a target angle between an image plane corresponding to the first image and a coordinate system in which the palm print image acquisition device is located; and determining, when the target angle is larger than a set angle threshold, a first image type as the target image type to which the first image belongs.
17. 17 . The computer device according to claim 10 , wherein the determining a feature matching degree between the first embedded feature and each image embedded feature in the image feature set comprises: determining a cosine similarity between the first embedded feature and each image embedded feature in the image feature set; and determining the cosine similarity between the first embedded feature and the image embedded features as the feature matching degree between the first embedded feature and the image embedded feature.
18. 18 . The computer device according to claim 10 , wherein the first image is acquired in real time when execution of a target service is triggered; and the method further comprises: obtaining, when the identity recognition information determined for the object to which the first image belongs is object identity information of a target object, a service permission of the target object for the target service; and executing the target service for the target object based on the service permission of the target object for the target service.
19. 19 . A non-transitory computer-readable storage medium having a computer program stored therein, and the computer program, when executed by a processor of a computer device, causing the computer device to perform an image processing method including: obtaining a first embedded feature of a first image, the first image being a palm print image; recognizing a target image type to which the first image belongs; obtaining an image feature set associated with the target image type, the image feature set comprising image embedded features of target images of a plurality of objects, each object having respective object identity information; determining a feature matching degree between the first embedded feature and each image embedded feature in the image feature set; and determining, among the plurality of objects, object identity information of an object whose associated image embedded feature has a highest feature matching degree with the first embedded feature for an object to which the first image belongs.
20. 20 . The non-transitory computer-readable storage medium according to claim 19 , wherein the first image is acquired in real time when execution of a target service is triggered; and the method further comprises: obtaining, when the identity recognition information determined for the object to which the first image belongs is object identity information of a target object, a service permission of the target object for the target service; and executing the target service for the target object based on the service permission of the target object for the target service.

Description

CROSS-REFERENCE TO RELATED APPLICATIONS This application is a continuation application of PCT Patent Application No. PCT/CN2025/100628, entitled “IMAGE PROCESSING METHOD AND APPARATUS, COMPUTER DEVICE, COMPUTER-READABLE STORAGE MEDIUM, AND COMPUTER PROGRAM PRODUCT” filed on Jun. 12, 2025, which is based upon and claims priority to Chinese Patent Application No. 2024109478671, entitled “IMAGE PROCESSING METHOD AND APPARATUS, COMPUTER DEVICE, COMPUTER-READABLE STORAGE MEDIUM, AND COMPUTER PROGRAM PRODUCT” filed on Jul. 15, 2024, both of which are incorporated herein by reference in their entirety. FIELD OF THE TECHNOLOGY This application relates to the field of image processing technologies, and in particular, to an image processing method and apparatus, a computer device, a computer-readable storage medium, and a computer program product. BACKGROUND OF THE DISCLOSURE In the field of performing user identity recognition based on a palm print image, a standard and perfect palm print image of a user may be acquired in advance and stored as a base image of the user, and subsequently, user identity recognition may be performed by using the stored base image. However, in a specific process of performing user identity recognition, a palm print image acquired in real time is random. Compared with the prestored base image, the palm print image acquired in real time may probably have inconsistency in terms of the posture, style, or the like, causing a large quantity of invalid comparisons and low recognition efficiency, and causing inconsistency between the palm print image acquired from the user in real time and the prestored base image of the user. Consequently, accurate user identity recognition cannot be implemented. SUMMARY Embodiments of this application provide an image processing method and apparatus, a computer device, a computer-readable storage medium, and a computer program product, to improve accuracy of performing recognition on an identity of an object by using a palm print image. An embodiment of this application provides an image processing method performed by a computer device, the method including: obtaining a first embedded feature of a first image, the first image being a palm print image;recognizing a target image type to which the first image belongs;obtaining an image feature set associated with the target image type, the image feature set including image embedded features of target images of a plurality of objects, each object having respective object identity information;determining a feature matching degree between the first embedded feature and each image embedded feature in the image feature set; anddetermining, among the plurality of objects, object identity information of an object whose associated image embedded feature has a highest feature matching degree with the first embedded feature for an object to which the first image belongs. An embodiment of this application provides a computer device, including a memory and a processor, the memory having a computer program stored therein, and the computer program, when executed by the processor, causing the computer device to perform the image processing method according to the embodiment of this application. An embodiment of this application provides a non-transitory computer-readable storage medium, the computer-readable storage medium having a computer program stored therein, and the computer program, when executed by a processor of a computer device, causing the computer device to perform the foregoing image processing method. According to embodiments of this application, a to-be-recognized first image and a first embedded feature of the first image may be obtained, the first image being a palm print image, and a target image type to which the first image belongs may be recognized from a plurality of set image types; an image feature set associated with the target image type may be obtained; the image feature set including image embedded features of target images of a plurality of objects, the target images being palm print images that belong to the target image type, and each object having respective object identity information; a feature matching degree between the first embedded feature and each image embedded feature may be obtained; and identity recognition information for an object to which the first image belongs may be determined based on the object identity information of each object and the feature matching degree between the first embedded feature and the image embedded feature. It can be learned that according to the method provided in embodiments of this application, a specific target image type to which the first image belongs may be first recognized, so that identity recognition on the object to which the first image belongs may be implemented by using a specific image feature set associated with the specific target image type and an embedded feature (for example, the first embedded feature) of the first image. Recognition