基于区域形状的静脉图像特征提取与匹配

为了准确地对人的身份进行识别,提出了一种基于区域形状的静脉图像特征提取与匹配算法.静脉图像经预处理后得到二值图像,该算法首先对二值图像进行细化处理,得到了静脉的骨架信息;然后,标注4连通区域并寻找到与连通区域相连接的端点与交叉点;再利用最小距离法将连通区域的边缘逼近成若干条线段,将线段角度作为特征;最后,利用改进的最长公共子序列算法,进行了局部区域匹配,并利用改进的豪斯多夫距离算法进行整幅图像的匹配.实验表明,该算法获得的图像特征具有较高的区分度,识别效果受采集静脉图像中信息缺失的影响较小,正确识别率可达到96%以上.

Vein Image Feature Extraction and Matching Based on Regional Shapes

In order to recognize one’s identity accurately,an algorithm of feature extraction and matching based on regional shape was presented.The vein image was transformed into binary image through preprocessing first,the binary image was then thinned,and skeletal information of the vein image was obtained.Afterwards,the four connecting areas were labeled,then the endpoints and crossing points which are linked with the connecting area were found.The edge of the connecting area was approximated with several lines through the minimal distance method,and the angles of these lines were regarded as the feature of vein image.Finally,the local region was matched through the improved longest common subsequence method,and the global image was matched by the improved Hausdorff distance method.The experimental result shows that the acquired image feature by this algorithm has stronger distinguishing,the recognition result is affected less because of information missing in collecting vein images,and the correct recognition rate exceeds 96%.