针对透射式近红外光手掌静脉成像技术中手掌不同区域厚度差异大而导致静脉成像质量差的问题，提出了一种对手掌分区域多次曝光获取静脉血管图像法.根据近红外光照明条件下人体手掌的光学模型，结合CCD对光强的动态响应，计算出照明光强和手掌厚度的指数关系.首先，在手掌不同厚度区域，使用波长为850 nm、光强大小不同的三种近红外光照明，分别获得三种光强的手掌静脉图像；然后，对得到的静脉图像分别进行分割增强处理；最后，用加权渐变拼接方法，得到完整清晰的手掌静脉图像.实验结果表明，该融合方法能够有效弥补透射法单一光强照明无法得到完整手掌图像的不足，所得到图像各部分的对比度都得到显著提高，同时也比反射法得到图像的对比度高.该方法可以很好地用在静脉穿刺、生物识别上，在未来信息化的安全性、身份识别功能上有重要意义.

Aiming at the problem of poor imaging quality due to the different thicknesses of the same palm, a method of getting the palm vein images was proposed based on multiillumination using nearinfrared region (NIR) light. The exponential relationship between illumination intensity and palm thickness was figured out according to the optical model of the human palm and dynamic range of the CCD. Firstly, three different intensities of NIR light with the same wave length of 850 nm were be used as illumination in the experiment to obtain the palm vein images respectively. Secondly, palm vein images were divided into several subimages which are with high contrast. Next, the adaptive equalization was employed to enhance palm vein images. Finally, the method of weighting gradient splicing was applied to obtain the integrated palm vein images. Experimental result shows that the fusion method can improve the contrast of each part of palm vein images effectively compared with the transmission method with single illumination intensity and the reflection method. This method can be used in several application fields, such as venipuncture, biometrics and is of great value in the areas of identification recognition and the information security in the future.