Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2019-04-01 Cooperative journals: 《计算机应用研究》
Abstract： For the problem of the palmprint recognition algorithm had less research on the recognition of color palmprint images, this paper proposed a new BP neural network color palmprint image recognition algorithm based on the analytical properties of Stein-Weiss function. The proposed method first constructs a Stein-Weiss function for each pixel in the color palmprint image. Then according to the analyticity of the Stein-Weiss function, sixteen eigenvalues of the corresponding pixel are calculated. These eigenvalues are used as the input data of the BP neural network. These data can be classified and learned through the self-learning ability of BP neural network. Then the palmprint edge is obtained through generalization ability of BP neural network. Finally, the pairwise attributes are extracted from palmprint edge, and the feature library is built. The palmprint is recognized by the paired geometric histogram intersection algorithm. The experimental results show that the proposed algorithm can extract finer palmprint faster and the recognition rate is higher compared with the previous grayscale palmprint image recognition algorithm. And it has strong robustness to the interference of rotation and noise.
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