To avoid the difficulty of obtaining the palm vein images,and low quality of the images along with the complex palm region locating methods,this paper proposes a device for acquiring palm vein images. The quality of acquired images is assessed by 2D image entropy and local 2D entropy. Based on the feedback image quality,the brightness of near infrared light emitting diodes(LEDs)is controlled and some parameters of the camera are set, then the image is recaptured until high quality palm vein is achieved. Those images acquired are used for fast ex⁃traction of the palm region of interest(ROI),and the following image processing algorithms. The images are as⁃sessed by the accelerating implementation method applying to Field Programmable Gate Array(FPGA)platform, and ROI extraction uses local image fast discrimination method. In conclusion,this study provides a method to ac⁃quire the palm vein images using 2D entropy assessment,coordinated with feedback control Pulse Width Modulation (PWM)output. The efficacy gets improved compared to the method of present stage,such as acquiring images’gra⁃dation characteristics,vein characteristics,in the meantime,the sharp images reduce the computation cost of extrac⁃tion ROI and increase the performance of processing.%针对手掌静脉图像获取困难，获取的手掌静脉图像质量欠佳以及手掌区域定位方法复杂的问题，提出了一种手掌静脉采集装置，使用该装置进行手掌静脉图像采集。采用基于图像二维熵和局部二维熵方法来评价采集的图像质量，并依据反馈的评价结果作为依据，自适应控制近红外LED的亮度和摄像头的参数，重新采集直到获得高质量的手掌静脉图像。并将获得的高质量图像作为手掌感兴趣区域（ROI）提取及后续的图像处理算法的输入图像。本文的图像质量评价方法采用改进型适用于现场可编程门阵列（FPGA）平台的加速实现方法，ROI提取通过构建局部图像快速判别和定位。实验结果表明，使用二维熵评价图像的方法配合反馈控制PWM波的输出所采集的手掌静脉图像，比现有阶段方法采集的图像在灰度特性、静脉特征的效果方面得到提升，同时获得的图像减少了后处理中ROI提取算法的计算量。
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