关键词: 生物识别, àtrous-Contourlet变换, 不变矩, 特征提取, 统计特征

Abstract: In order to improve the speed and accuracy of palmprint identification system and overcome the weakness of Contourlet transform in dealing with high-dimensional signals, a novel identification algorithm of palmprint feature was proposed. Firstly, the àtrous-Contourlet transformation for palmprint image was decomposed to obtain high frequency coefficients and low frequency coefficients in the different sub-band of different direction. Then, different feature weighting coefficients according to the statistical characteristics extracted from different frequency domains were chosen, which were calculated to get some new invariant moments vectors. Finally, the palmprint identification was achieved. The experimental results show that the method here is more effective in matching than wavelet moment algorithm, Hus invariant moment algorithm and Contourlet algorithm.

Key words: biological identification, àtrous-Contourlet transform, invariant moment, feature extraction, statistical characteristic