关键词: 非负矩阵分解, 局部特征提取, 特征基图像, 掌纹识别, 径向基概率神经网络（RBPNN）分类器

Abstract: A palmprint recognition method based on Non-negative Matrix Factorization（NMF） and Radial Basis Probabilistic Neural Network（RBPNN） is proposed. NMF is an efficient local feature extraction algorithm of images, and it can obtain high recognition rate in image classification task. Considered PolyU palmprint image database, the palm features are extracted by using several algorithms, such as NMF, Local NMF（LNMF）, Sparse NMF（SNMF）, and NMF with Sparseness Constraints（NMFSC） et al. And these feature basis images extracted are analyzed and compared. On the basis of feature extraction, the RBPNN classifier is utilized to classify palmprint features, and the classification results show that the RBPNN model has better palmprint recognition property. Compared classification results obtained by different algorithms, it is clear to see that the palmprint recognition results based on RBPNN and NMF are indeed efficient, and these algorithms behave certain theory research meaning and application in practice.

Key words: non-negative matrix factorization, local feature extraction, feature basis image, palmprint recognition, radial basis probabilistic neural networks classifier