A 3D Palmprint Recognition Method Based on Block Statistical Features and Joint Representation

Abstract

The invention discloses a three-dimensional palm print identification method based on a partitioning statistical characteristic and joint expression. A sample image of a three-dimensional palm print, is equally divided into a plurality of subareas, for each subarea, the surface type of the palm print is calculated firstly, then the surface types of palm prints in each subarea is counted by use of a histogram, finally, surface type histograms of each subarea are spliced to be taken as a characteristic description operator of a palm depth image, and classification is carried out by use of a joint expression frame, such that the identification efficiency and the accuracy are improved, the method can be applied to occasion with strict requirements for identity identification, and the problem of aligning deviations among multiple three-dimensional palm print samples is effectively solved.

Description

technical field [0001] The invention belongs to the field of pattern recognition, and relates to a method for verifying identity information, in particular to a palmprint recognition method. Background technique [0002] In recent years, the industry and academia have continuously been committed to improving the verification effect of identity information to meet the stringent requirements for identifying people in many different fields such as access control, aviation security, and electronic banking. Methods based on biometric identification are attracting more and more attention, and palmprint recognition is one of the most representative biometric identification methods. The palmprint recognition method has many advantages such as high discrimination, strong robustness, and user-friendliness. Palmprint refers to the skin texture on the surface of the palm, which mainly includes two types of features: friction ridges and flexion lines. These two characteristics are unch...

AI Technical Summary

Problems solved by technology

Aiming at the problem that in the past 3D palmprint matching process, the palmprint to be verified and the sample data set need to be matched one by one, and the efficiency is greatly reduced with the increase of the capacity of the sample data set, a joint representation framework is used to carry out the 3D palmprint to be tested. One-to-many recognition; Aiming at the slight alignment error after 3D palmprint matching, a description operator based on block statistical features is used

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