Abstract: A novel palmprint recognition algorithm based on information entropy under GLBP (EGLBP) was proposed in this paper,and it was first introduced into palmprint recognition．At the same time,in order to improve the recognition accuracy and reduce the complexity of the algorithm,information entropy was used to measure the information of palmprint.The bigger the entropy is,the more information is contained．Firstly,the images were decomposed though Gabor transform,and their information entropies were calculated．Then several small images were removed．Secondly, LBP feature extraction for each block was processed using the block idea,and the features were parallelly fused．Finally,chi-square distance was used to determine palmprint category．After PolyU palmprint database’s verification of the region of interest, compared with the traditional palmprint recognition algorithm, EGLBP algorithm has a recognition rate of 99.89% and a recognition time of 113.9ms,demonstrating its superiority and effectiveness.

Key words: Palmprint recognition,Gabor transform,Local binary pattern,Information entropy,Block thought,EGLBP algorithm