Palmprint Recognition Using Wavelet Decomposition and 2D Principal Component Analysis

摘要：

In this paper, a novel method using wavelet decomposition and 2D Principal component analysis (2DPCA) for palmprint recognition is presented. Firstly, 2D wavelet transform is adopted to obtain different level of wavelet coefficients of the original palmprint image; secondly 2DPCA is applied on the low-frequency that contains most discrimination information of the original palmprint image. One criterion that not all PCs are useful for palmprint recognition is demonstrated and a rule for selecting 2D PCs is proposed. Lastly, this algorithm is tested on the PolyU palmprint image database and the experimental result is encouraging and achieves comparatively high recognition accuracy and more computationally efficient than using other feature extraction techniques such as principal component analysis and independent component analysis.

作者: Jiwen Lu Erhu Zhang Xiaobin Kang Yanxue Xue Yajun Chen

作者单位: Department of Information Science Xian University of Technology Xian, Shannxi, China

会议类型: 国际会议

会议名称: 2006 International Conference on Communications,Circuits and Systems(第四届国际通信、电路与系统学术会议)

会议地点: 广西桂林

会议语种:英文

页码: 2133-2136

在线出版日期: 2006-06-25（万方平台首次上网日期，不代表论文的发表时间）