Large-scale palm print coding and comparison method

Abstract

The invention relates to a large-scale palm print coding and comparison method. The method comprises: image rotation and translation are carried out on a large-scale registered palm print image and a to-be-identified palm print image according to a unified coordinate system; each palm print image is cut into a plurality of palm print image blocks according to a certain dimension, wherein palm print image blocks cut from the registered palm print image are named as registered palm print image blocks and palm print image blocks cut from the to-be-identified palm print image are named as to-be-identified palm print image blocks; for each palm print image block, a feature matrix and a detailed node matrix are constructed; a palm print fast screening tree is constructed; and with the feature matrixes and detailed node matrixes of the palm print image blocks, all to-be-identified palm print image blocks are retrieved in the fast screening tree to obtain registered palm print image blocks having feature evaluation indexes similar to those of the to-be-identified palm print image blocks, and on the basis of an ownership between the palm print image blocks and the palm print images, a registered palm print image most similar to the to-be-identified palm print image is selected as a finally identified palm print image.

Description

technical field [0001] The invention provides a large-scale palmprint coding and comparison method, which belongs to the field of biological feature recognition, and specifically relates to a palmprint recognition method. Background technique [0002] With the continuous advancement of computer technology and information processing and identification technology, palmprint recognition technology has developed rapidly and has become a mature and acceptable biometric identification technology, which can be used in public security, network management, social security, Electronic access control and other widely used technologies in many fields have important theoretical research significance and market application value. [0003] Palmprint recognition technology is divided into two processes: (1) palmprint feature extraction process. By reading the palmprint image, the palmprint area in the palmprint image is found, and the features in the palmprint area that can distinguish the...

AI Technical Summary

Problems solved by technology

[0005] In the large-scale palmprint recognition scenario, the above methods are not suitable: (1) In the process of palmprint feature extraction, only using the above local and overall features is not enough to accurately distinguish the palmprint features of large-scale palmprint images, which leads to Recognition accuracy drops significantly, so that the so-called "big library accuracy attenuation" effect occurs, and the present invention then additionally constructs stable features for distinguishing large-scale palmprints, thereby significantly improving recognition accuracy; (2) the main stream disclosed in patents and documents The palmprint recognition methods all use the idea of ​​"one-by-one comparison" between the palmprint image to be recognized and the registered palmprint image, so it takes a lot of time

Images