The Research And Application On Palmprint Recognition Technology

Today, with the rapid development of information and internet all over the world, information security is extraordinarily important, especially, personal identification technology. Because biological feature identification technology has unique stability, uniqueness and convenience, it is applied more and more broadly. As palmprint is typical of ease acquisition, and its major feature is apparent, stability and divisibility, palmprint automatic identification is a very potential identification technology.However, the research and application of biological feature identification based on palmprint are very few due to the complexity, diversity and variableness of palmprint. In present, most research of plamprint recognition is based on the feature of physics, structure or geometry. According to the speciality of palmprint, this paper proposes a recognition method based on algebraic feature. In order to extract the global feature of palmprint by PCA (Principal Component Analysis) , K-L transform and NN (Linear Neural Network) method is presented. As for classification, this thesis proposes LD (least distance) and BPNN(Back Propagation Neural Network) method. Finally, combining the two extraction methods with the two classification methods, the thesis put forward four models of palmprint recognition: K-L+LD model, K-L+NN model, NN+LD model and NN+NN model. The experiments show the accuracy, efficiency and the fault tolerance ability of these models. In terms of their characteristic, we can apply them in various fields.