融合水平梯度与局部信息强度的掌纹识别算法  

Palmprint Recognition Algorithm of Integrating Horizontal Gradient and Local Information Intensity

作　　者：赵志刚[1] 吴鑫[1] 张维忠[1] 赵毅[1] 洪丹枫[1] 潘振宽[1] 

机构地区：[1]青岛大学信息工程学院,青岛266071

出　　处：《计算机科学》2015年第6期317-320,F0003,共5页Computer Science

基　　金：国家自然科学基金(61170106);山东省科学技术发展计划项目(2012YD01058)资助

摘　　要：掌纹纹线特征是掌纹最有效的特征。由于在采集掌纹时不可避免地会产生尺度不一致、细微的旋转或平移等问题,使得准确地提取以及描述纹线特征成为掌纹识别的一大难点。针对这一问题,提出了一种融合水平梯度与局部信息强度的掌纹识别算法(Horizontal Gradient-Local Information Intensity,HG-LII)。首先,使用不同的均值滤波模板消除细小、不规则、不稳定的掌纹纹线特征,对处理后的图像使用水平梯度算子得到水平方向的梯度图像,并进行二值化;其次使用分块思想计算掌纹纹线的信息强度,并将其作为特征向量;最后采用卡方距离进行匹配,判断掌纹所属类别。在PolyU掌纹库上的实验结果表明,该算法识别率达到99.89%,与传统的提取纹线算法相比,识别率有明显的提高,表明了该算法的有效性。The palm ridge characteristic is the most effective feature of palmprint. At the acquisition time,,~alm will pro duce problems of inconsistent scale, rotation, translation and so on, which make accurately extracting and descrihing ridge feature become a major difficulty in palmprint recognition. To solve these problems,a novel palmprint recognition algorithm based on a fusion of horizontal gradient orientation and local information intensity（referred FHOG-LII） was proposed. First, we used the mean filter with different templates to remove fine,irregular and unstable characteristics of palm ridge,and used horizontal gradient operator to handle the processed image the processed image and then made im age binarization. Secondly, we used the thoughts of blocks to calculate information intensity of palm ridge and made it as feature vector. At last,we used the chi-square distance to match them. Experimental results on PolyU palmprint data base show that the proposed method can obtain state-of-the-art recognition accuracy（99. 89%）. Compared with some traditional methods, the recognition rate improves significantly, indicating the effectiveness of the proposed algorithm.

关 键 词：掌纹识别 二值化 均值滤波 水平梯度算子 信息强度 卡方距离 

分 类 号：TP391.4[自动化与计算机技术—计算机应用技术]