Application of Principal Component Analysis to Palmprint Images Recognition
主成分分析法在掌纹图像识别中的应用

The palmprint recognition is a new biometric technology, which has a good prospect of applications in the areas of network security, identity authentication etc. In this paper, the principal component analysis method is applied to palmprint image feature extraction, and the differences between the traditional principal component analysis(PCA) and the weighted principal component analysis(WPCA) in addressing the palmprint image are explained. According to the experimental results of two methods on two databases, PCA has a higher precision of palmprint recognition than WPCA, and the affection of light condition is weakened by WPCA.