基于轮廓与边缘纹理特征融合的掌纹识别  

Palm Print Recognition Based on Contour Feature and Edge Texture Feature Fusion

作　　者：李川[1] 罗金生[1] 刘传辉[1] 

机构地区：[1]绵阳职业技术学院信息工程系,四川绵阳621000

出　　处：《兵工自动化》2015年第11期52-56,共5页Ordnance Industry Automation

基　　金：四川省教育厅自然科学重点项目(15ZA0369)

摘　　要：为了增强掌纹图像信息的分析和提取能力,提出了一种基于轮廓与边缘纹理特征融合的掌纹识别算法。该算法分别将灰度直方图和差分盒子维算法作用于掌纹图像的低频和高频成分,提取图像的轮廓和边缘纹理特征,然后并联融合二者特征向量进行匹配。通过香港理工大学Poly U掌纹图像数据库的验证,算法识别精度为99.56%,特征提取和匹配时间为56 ms,满足识别精度和实时性要求,且算法复杂度和造价低,具有较高的工程应用价值。In order to enhance the ability of analysis and extraction of palm print image information, this paper proposes a novel palm print recognition method based on contour feature and edge texture feature fusion. We choose grey histogram and differential box counting to work on low-frequency features and high-frequency, and extract its contour feature and edge texture features. Then, making two features fusion in parallel. Experimental results on Poly U palm print experiment and compares with the traditional palm print recognition algorithm, the proposed method can obtain 99.56% recognition accuracy and the time of feature extraction and matching is only 56 ms, meeting the real-time requirements. At the same time, with low algorithm complexity and low cost in the actual demand, and has high value of engineering application.

关 键 词：轮廓特征 边缘纹理特征 灰度直方图 差分盒子维 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]