Abstract：As a new kind of identity authentication technology, finger vein recognition has more merits than other biometric feature authentication system. Therefore, it has a vast application prospect. The algorithm based on wavelet combined with Principal Component Analysis (PCA) transformation and LDA transformation is proposed. It not only overcomes the disadvantage of the single feature recognition, but also solves the lowspeed problem of common template matching. Experimental results indicate that the proposed method can provide fast and accurate identification, and the results are satisfactory.
王科俊，袁智. 基于小波矩融合PCA变换的手指静脉识别*[J]. 模式识别与人工智能, 2007, 20(5): 692-697.
WANG KeJun, YUAN Zhi. Finger Vein Recognition Based on Wavelet Moment Fused with PCA Transform. , 2007, 20(5): 692-697.
[1] Miura N, Nagasaka A, Miyatake T. Feature Extraction of FingerVein Patterns Based on Repeated Line Tracking and Its Application to Personal Identification. Machine Vision and Applications, 2004, 15(4): 194203 [2]Ridler T W, Calvard S. Picture Thresholding Using an Iterative Selection Method. IEEE Trans on Systems, Man and Cybernetics, 1978, 8(8): 630632 [3]Ding Yuhang, Zhuang Dayan, Wang Kejun. A Study of Hand Vein Recognition Method // Proc of the IEEE International Conference on Mechatronics and Automation. Niagara Falls, Canada, 2005, Ⅳ: 21062110 [4]Ji Hu, Sun Jixiang, Yao Wei. Wavelet Moment for Images. Journal of Circuits and Systems, 2005, 10(6): 132136 (in Chinese) (季 虎,孙即祥,姚 伟.图像的小波矩.电路与系统学报,2005, 10(6):132136)
2007, Vol. 20 
