Robust Palmprint Recognition Base on Touch-Less Color Palmprint Images Acquired

Haifeng Sang,Yueshi Ma,Jing Huang

doi:10.4236/jsip.2013.42019

Abstract

In order to make the environment of palmprint recognition more flexible and improve the accuracy of touchless palmprint recognition. This paper proposes a robust, touchless, palmprint recognition system which is based on color palmprint images. This system uses skin-color thresholding and hand valley detection algorithm for extracting palmprint. Then, the local binary pattern (LBP) is applied to the palmprint in order to extract the palmprint features. Finally, chi square statistic is used for classification. The experimental results present the equal error rate of 3.7668% and correct recognition rate of 97.0142%. Therefore the results show that this approach is robust and efficient in color palmprint images which are acquired in lighting changes and cluttered background for touch-less palmprint recognition system.

Highlights

Palmprint recognition is a biometric technology, which exploits the effective information on our palm to separate different persons
This paper proposes a robust, touchless, palmprint recognition system which is based on color palmprint images
The results show that approach is robust and efficient in color palmprint images which are acquired in lighting changes and cluttered background for touch-less palmprint recognition system

Summary

Introduction

Palmprint recognition is a biometric technology, which exploits the effective information on our palm to separate different persons. One of the important considerations in the contactless setting is how the hand can be detected and segmented from the background. In order to segment the hand from the background, Doublet et al (2007) [2], applied more complicated machine learning tool like neural networks to model the human skin color, but this paper did not propose a palmprint recognition approach for variant. The design and development of contactless palmprint recognition system is challenging. It brings an unstable environment for imaging. In order to solve the problem that contactless palmprint recognition system is challenging, this paper attempts to use the following methods to solve this problem. 1) Skin-color thresholding: Segment the hand image from the background by using the skin-color thresholding method. 4) Feature matching: Feature matching was performed by using chi square statistic

ROI Location

Feature Extraction and Matching

Sources of Experiment Data

Discussion

Conclusions