近日，实验室硕士生Kashif Shaheed的一篇论文“Novel image quality assessment and enhancement techniques for finger vein recognition”（作者：Kashif Shaheed、杨璐、杨公平、Imran Qureshi、尹义龙）被2018 International Conference on Security, Pattern Analysis, and Cybernetics（EI收录国际会议）录用，并获得大会最佳论文奖提名奖。

论文提出了一种手指静脉图像质量评价方法及一种图像质量增强方法。首先，对手指静脉图像提取梯度、信息容量等质量特征；然后使用决策树对图像质量进行分类（低质量图像和高质量图像）；最后，使用改进的多尺度Retinex滤波器和高斯滤波器对低质量图像进行增强。在自建手指静脉图像质量评价数据库上验证了图像评价方法和增强方法的有效性。

Recently, one paper of Kashif Shaheed, titled ‘Novel image quality assessment and enhancement techniques for finger vein recognition’, was accepted by 2018 International Conference on Security, Pattern Analysis, and Cybernetics, and Best Conference Paper Award Finalist was presented to this paper. Congratulation to Kashif Shaheed!

This paper proposed one finger vein image quality assessment method and one finger vein image enhancement method. In the proposed methods, some image quality features were firstly extracted, and then the decision tree was used to classify the finger vein images into low-quality class and high-quality class. Lastly, the low-quality images were enhanced by one improved multiscale Retinex filter and Gaussian filter. The experimental results on one self-built finger vein database proved the efficacy of the proposed methods.