A New Palm-Print Image Feature Extraction Method Based on Wavelet Transform and Principal Component Analysis

摘要：

In recent years, as one of the biometric identification technology, palm-print identification has received many reseachers attention. To solve the key problem of palm-print recognition — feature extraction, we propose a new method, which based on wavelet transform and principal component analysis. In general, we use wavelet transform to deal with palm print images and extract high-dimensional wavelet energy features, then reduce the dimensionality of high-dimensional wavelet energy features through principal component analysis, and remain the original feature energy maximally. The features extracted by this method not only reflect palm-print images information maximally, but also achieve the goal of data dimensionality reduction. Experiments show, the correct recognition rates of new method are much higher than those traditional

关键词： Palm-print Recognition feature extraction wavelet transform Principal component analysis.

作者: Jia wei Li Ming Sun

作者单位: China Agriculture University,Beijing China

会议类型: 国际会议

会议名称: The 4th IFIP International on Computer and Computing Technologies in Agriculture and the 4th Symposium on Development of Rural Information(第四届国际计算机及计算机技术在农业中的应用研讨会暨第四届中国农业信息化发展论坛 CCTA 2010)

会议地点: 南昌

会议语种:英文

页码: 39-46

在线出版日期: 2010-10-22（万方平台首次上网日期，不代表论文的发表时间）