Block Statistic for Palmprint Recognition Based on High Frequency Coefficients under Wavelet Transform
Palmprint recognition for identification provides a new scheme for information security.This paper presents a block statistic method based on high frequency coefficients under wavelet transform for palmprint identification.Firstly,the method decomposes region of interest (ROI) of the palmprint with the wavelet transform.Then it blocks the high-frequency sub-image.The mean and the variance for each sub-block are found.All the means and the variances constitute feature vector for the image.At last the nearest neighbor classifier is used to classify the images.The method was tested on the basis ofUST palmprint image database.From the experimental results,the method can satisfy the uses without excessive demands for collection images.
biometrics recognition block statistic Wavelet transform high-frequency coefficients
Yuqin Liu Weiqi Yuan Jinyu Guo
Computer vision Group,Shenyang University of Technology,Shenyang Liaoning,China;School of Informatio Computer vision Group,Shenyang University of Technology,Shenyang Liaoning,China School of Information Engineering,Shenyang University of Chemical Technology,Shenyang Liaoning,China
国际会议
沈阳
英文
1287-1291
2012-09-07（万方平台首次上网日期，不代表论文的发表时间）