目前的手掌静脉识别系统均采取主动光源来获取掌脉图像，光源波长的选择直接影响掌脉图像的清晰度与识别性能。典型的掌脉识别成像波长为760，850，890，940 nm，但没有指出哪种波长识别性能最佳。从两个角度解决此问题，从识别特征提取角度，建立了基于Fisher判别率的掌脉成像清晰度模型，对4种波长拍摄的掌脉清晰度进行比较；从特征匹配角度，以3种典型的生物特征识别算法对4种波长拍摄的掌脉图像进行识别性能比较。在包含4种波长共2400幅掌脉图像的自建图库中进行实验，模型选择和典型算法实验结果都表明，850 nm优于其他3种波长。证明了850 nm拍摄的掌脉图像的识别性能最佳。

Most of current palm vein recognition systems use an active light source to acquire images. The choice of light-source wavelength directly affects the definition of palm vein image and recognition performance. Typical wavelength of palm vein recognition is 760, 850, 890, 940 nm, while few works have been done on investigating which one is the optimal wavelength for palm vein recognitions. It is solved from two angles. From the angle of feature extraction, the model of palm vein image definition is established and palm vein definition of the four wavelengths is compared according to the model. From the angle of feature matching, the recognition performance of palm vein image with four wavelengths separately by three typical biological identification algorithms is compared. The experiment was done in a self-build database including 2400 palm vein images with four kinds of wavelength. The experiment result of the model and 3 algorithms show that 850 nm is the optimal wavelength. Wavelength of 850 nm achieves higher palm vein recognition performance than the other three wavelengths.