Palmprint recognition based on isodata clustering algorithm
This paper analyzes the palmprint textures with a multi-resolution method. Texture feature vectors of palmprint are extracted by wavelet transformation. With the texture feature, isodata clustering method is used to achieve classification of the Feature vectors. Based on the classification, euclidean distance within-class and between-class are calculated to match the feature. Experimental result illustrates that the proposed approach for palmprint recognition is effective.