基于UDCT和三角形测量特征融合的手背静脉识别

摘要

A new approach to palm-dorsal vein recognition based on the feature fusion is presented in this paper.After palm-dorsal image preprocessing and ROI (Region Of Interest) extraction,we use UDCT (Uniform Discrete Curvelet Transform) of the Curvelet Transform on ROI,and encode the Curvelet coefficients phase variance,and evaluate the Chi-square distance of coding histogram for vein recognition.When the distance between and threshold is large,we get the recognition result.Otherwise,this paper detects the skeleton of the hand vein,and uses the ending point and the crossing point of the extracted vein skeleton as the feature point,then measure the triangle side by the Triangulation algorithm.At last,this paper calculates the matching distance by the weighted average method.This approach improves recognition ratio and avoids the cost time noise problem increase sharply.%提出了一种基于特征融合的手背静脉识别算法,首先对手背静脉图像感兴趣区域进行预处理,然后采用均衡离散曲率波变换对感兴趣区域进行变换,接着对变换系数进行相位编码,并计算编码统计直方图的卡方距离,当此距离与阈值相差较大时,得到识别结果；否则,对预处理后的图像提取静脉骨架,确定相关的特征点,通过三角测量法来计算匹配距离,对和采用加权平均法来获得最终的识别结果.该方法在识别时间没有明显增加的情况下,而识别的效果却得到了提高.