计算机工程与应用2011，Vol.47Issue(24)：17-19,22,4.DOI:10.3778/j.issn.1002-8331.2011.24.005
小波变换与分块统计在掌纹识别中的应用
Application of wavelet transform and block statistic to palmprint recognition
摘要
Abstract
Palmprint recognition for identification provides a new scheme for information security.This paper presents a combination method of transform domain and statistic domain for palmprint identification.The method filters Region Of Interest (ROI) of the palmprint with median filtering and decomposes it into several sub-images with the wavelet transform.Then it blocks the high-frequency sub-image.The mean and the variance of high-frequency coefficients for each sub-block are found. Their combination constitutes feature vector for the image.The nearest neighbor classifier is used to classify the images.The method is tested on the basis of UST palmprint image database.From the experimental result of 95.5% recognition rate,the method is better than the sub-space methods that are used for palmprint identification at present.关键词
生物特征识别/掌纹识别/小波变换/分块统计/高频系数Key words
biometrics recognition/palmprint recognition/wavelet transform/block statistic/high-frequency coefficients分类
信息技术与安全科学引用本文复制引用
刘玉芹,苑玮琦,郭金玉..小波变换与分块统计在掌纹识别中的应用[J].计算机工程与应用,2011,47(24):17-19,22,4.基金项目
国家自然科学基金(the National Natural Science Foundation of China under Grant No.60972123) （the National Natural Science Foundation of China under Grant No.60972123）
辽宁省教育厅科研项目(No.L2010436). （No.L2010436）
