Block Statistic for Palmprint Recognition Based on High Frequency Coefficients under Wavelet Transform

Abstract:

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 of UST palmprint image database. From the experimental results, the method can satisfy the uses without excessive demands for collection images.

• Periodical: Applied Mechanics and Materials (Volumes 182-183)
• Pages: 1287-1291
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.182-183.1287
• Online since: June 2012
• Authors: Yu Qin Liu, Wei Qi Yuan, Jin Yu Guo
• Keywords: Biometrics Recognition, Block Statistic, High-Frequency Coefficients, Wavelet Transform (WT)

References

[1] Wang Yan-xia, Ruan Qiu-qi. A Method of Line Structure Features Representation and Matching of Palmprint[J]. Journal of Electronics & Information Technology, 2008，30(6)：1281－1285.

DOI: 10.3724/sp.j.1146.2006.01871

[2] D Zhang, W Kong, J You. Online Palmprint Identification [J]. IEEE Trans PAMI, 2003, 25 (9): 1041-1050.

[3] Li Qiang, Qiu Zheng-ding, Sun Dong-mei, Liu Lu-lu. Online Palmprint Identification Based on Improved 2D PCA[J]. ACTA ELECTRONICA SINICA, 2005，33(10)：1886-1889.

[4] Lu Guangming，Zhang David，Wang Kuanquan. Palmprint Recognition Using Eigenpalms Features [J]. Pattern Recognition Letters，2003，24(9/10)：1463-1467.

DOI: 10.1016/s0167-8655(02)00386-0

[5] Wu Xiangqian，Zhang David，Wang Kuanquan. Fisherpalms based palmprint recognition[J]. Pattern Recognition Letters，2003，24(15)：2829—2838.

DOI: 10.1016/s0167-8655(03)00141-7

[6] Sang Haifeng, Yuan Weiqi, Zhang Zhijia, Huang Jing. Palmprint recognition based on two-dimensional principal component analysis [J]. Chinese Journal of Scientific Instrument, 2008，29(9)，：1929-(1933).

[7] Guo Jin-yu, Yuan Wei-qi. Palmprint recognition based on independent component analysis [J]. Opto-Electronic Engineering, 2008, 35(3): 136-139.

[8] HUANG Shen，XU Cheng，QU Jing-hui，LIAO Qi-mei. Principle Line Extraction and Restoration Based on Wavelet Theory [J]. Journal of Image and Graphics, 2006, 11(8): 1139-1149.

[9] Wu Jie，Qiu Zhengding，Sun Dongmei. A Feature Extraction Algorithm Based on Wavelet Transform and Moment Invariant[C]. 4th Joint Academic Conference on Signal and Information Processing: 2005: 191-195.

[10] Su Xiaosheng, Lin Xirong, Ding Tianhuai, Zhou Yunlong, Song Jiong. Palmprint Feature Extraction Based on Wavelet Transform[J]. J Tsinghua Univ, 2003，43(8)：1049-1055.

[11] Helen. UST Hand Image Database [DB/OL]. http: /visgraph. cs. ust. hk/biometrics/Visgraph_web/index. html, (2003).