Please wait a minute...
浙江大学学报(工学版)
J4  2009, Vol. 43 Issue (8): 1412-1418    DOI: 10.3785/j.issn.1008-973X.2009.
电子、通信与自动控制技术     
鲁棒的掌纹图像特征提取方法
竺乐庆1,2,陈文智1,幸锐1,张三元1
(1.浙江大学 计算机科学与技术学院, 浙江 杭州 310027； 2.浙江工商大学 计算机与信息工程学院, 浙江 杭州 310018)
A robust method to extract features from palm image
 DU Le-Qiang1,2, CHEN Wen-Zhi1, NIE Dui1, ZHANG San-yuan1
 全文: PDF(1555 KB)   HTML
摘要：

提出了一种基于低分辨率彩色图像的鲁棒的掌纹图像特征提取方法.采用均值平移算法对彩色图像帧中像素进行聚类,应用Ostu二值化方法分割出手掌,并提取出有效掌纹区域.采用KLT角点检测算法提取出有效掌纹区域内的特征点,给每个特征点赋予方向,并根据局部区域特征构造方向不变的特征向量,所有特征点及其特征向量的集合构成了掌纹图像特征.在识别时只须在两个特征点集之间查找匹配对应,并通过随机采样一致性检验最大一致集中内点个数是否大于自适应域值来确定两个手掌是否匹配.利用该算法对网络摄像头采集的手掌样本进行了实验测试,获得了较高的识别精度与性能.该算法对手掌的距离、方向、姿势没有特殊要求,是一种鲁棒高效的掌纹图像特征提取方法.
Abstract:

A robust method was proposed to extract palmprint features from low resolution color images. Firstly, mean shift algorithm is used to cluster color blocks; secondly, Ostu binarization method is used for segmentation; thirdly, the feature points are extracted with KLT corner detector, to which an orientation is assigned according to the most fast varying gradient direction. The keypoint descriptor can be constructed relative to this orientation so that it’s invariant to image rotation. The location, orientation and rotation invariant local descriptors of keypoints make up of the features of a palm image. In recognition, testing palm features are matched to the template features for initial correspondences, then random sample consensus (RANSAC) is used to confirm the final matching. Plenty of experiments showed that palmprints could be recognized with high accuracy. The method has no limitation to palm rotation, very loose limitation to palm distance and pose, which further proves its robusticity.
出版日期: 2009-09-28
:  TP 391.41  
基金资助:

国家自然科学基金资助项目（60473106）；国家“863”高技术研究发展计划资助项目（2007AA01Z311，2007AA04ZA5）
通讯作者: 陈文智，男，副教授.     E-mail: chenwz@zju.edu.cn
作者简介: 竺乐庆（1972-），女，浙江嵊州人，博士，从事图像处理与嵌入式系统研究.
服务　　
把本文推荐给朋友
加入引用管理器
E-mail Alert
RSS
作者相关文章　　

引用本文:

竺乐庆, 陈文智, 幸锐, 等. 鲁棒的掌纹图像特征提取方法[J]. J4, 2009, 43(8): 1412-1418.

DU Le-Qiang, CHEN Wen-Zhi, NIE Dui, et al. A robust method to extract features from palm image. J4, 2009, 43(8): 1412-1418.

链接本文:

http://www.zjujournals.com/eng/CN/10.3785/j.issn.1008-973X.2009.    或    http://www.zjujournals.com/eng/CN/Y2009/V43/I8/1412

[1] YAMATO K, HARA Y. Fingerprint identification system by ravine thinning [J]. The Transactions of the IEICE, 1988, J71-D(2): 329-335.
[2] SHU W, ZHANG D. Automated personal identification by palmprint [J]. Optical Engineering, 1998, 37(8): 2359-2362.
[3] ZHANG D, KONG W K, YOU J, et al. Online palmprint identification [J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2003, 25(9): 1041-1050.
[4] NOH J S, RHEE K H. Palmprint identification algorithm using Hu invariant moments and Otsu binarization [C]∥ Proceedings of the Fourth Annual ACIS International Conference on Computer and Information Science. Washington DC: IEEE, 2005: 94-99.
[5]  ITO K, AOKI T, NAKAJIMA H, et al. A palmprint recognition algorithm using phase-based image matching [C]∥ 2006 IEEE International Conference on Image Processing. Atlanta: IEEE, 2006: 2669-2672.
[6]  LI W X, ZHANG D, XU Z Q. Palmprint recognition based on Fourier transform [J]. Journal of Software, 2002，5(13): 879-886.
[7] ZOU W M, ZHANG D, WANG K Q. Bidirectional PCA with assembled matrix distance metric for image recognition [J]. IEEE Transactions on Systems, Man and Cybernetics, Part B, 2006, 36(4): 863-872.
[8]  LU Y H, JIANG L K, KONG J, et al. An adaptive and robust hand-based personal identification [C]∥ IEEE Mediterranean Electrotechnical Conference. Benalmádena: IEEE, 2006: 494-497.
[9] OTSU N. A threshold selection method from gray-level histograms [J]. IEEE Transactions on Systems, Man, and Cybernetics, 1979, 9(1): 62-66.
[10] SHI J, TOMASI C. Good features to track [C]∥ IEEE Conference on Computer Vision and Pattern Recognition. Seattle: IEEE, 1994: 593-600.
[11] CHENG Y. Mean shift, mode seeking, and clustering [J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1995, 17(8): 790-799.
[12] FUKUNAGA K, HOSTETLER L D. The estimation of the gradient of a density function, with applications in pattern recognition [J]. IEEE Transactions on Information Theory， 1975, 21(1): 32-40.
[13] COMANICIU D, MEER P. Mean shift: a robust approach [J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2002, 24(5): 603-619.
[14] 李文新,夏胜雄,张大鹏,等. 基于主线特征的双向匹配的掌纹识别新方法[J]. 计算机研究与发展, 2004, 41(6): 996-1002.
LI Wen-xing, XIA Sheng-xun, ZHANG Da-peng, et al. A new palmprint identification method using bi-directional matching based on major line features [J]. Journal of Computer Research and Development, 2004, 41(6): 996-1002.
[15] TOMASI C, KANADE T. Detection and tracking of point features [R]. Pittsburgh: Carnegie Mellon University, 1991.
[16] LOWE G D. Distinctive image features from scale-invariant keypoints [J]. International Journal of Computer Vision, 2004, 60(2): 91-110.
[17] FISCHLER A M, BOLLES R C. Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography [J]. Communications of ACM, 1981, 24(6): 381-389.
[18] LOWE G D. Local feature view clustering for 3D object recognition [C]∥ Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. Kauai: IEEE, 2001: 682-688.
[1] 杨玉婷, 史玉回, 夏顺仁. 基于讨论机制的头脑风暴优化算法[J]. J4, 2013, 47(10): 1705-1711.
[2] 朱晓恩, 郝欣, 夏顺仁. 基于Levy flight的特征选择算法[J]. J4, 2013, 47(4): 638-643.
[3] 孙创日,甄帅,夏顺仁. 基于吸引区域的多模态脑磁共振图像仿射配准[J]. J4, 2012, 46(9): 1722-1728.
[4] 谢迪, 童若锋, 唐敏, 冯阳. 具有高区分度的视频火焰检测方法[J]. J4, 2012, 46(4): 698-704.
[5] 李启雷, 金文光, 耿卫东. 基于无线惯性传感器的人体动作捕获方法[J]. J4, 2012, 46(2): 280-285.
[6] 戴渊明, 韦巍, 林亦宁. 基于颜色纹理特征的均值漂移目标跟踪算法[J]. J4, 2012, 46(2): 212-217.
[7] 刘晨彬,潘颖,张海石,黄峰平,夏顺仁. 基于磁共振图像的脑瘤MGMT表达状况检测算法[J]. J4, 2012, 46(1): 170-176.
[8] 钱诚, 张三元. 适用于目标跟踪的加权增量子空间学习算法[J]. J4, 2011, 45(12): 2240-2246.
[9] 曹颖, 郝欣, 朱晓恩, 夏顺仁. 基于自动随机游走的乳腺肿块分割算法[J]. J4, 2011, 45(10): 1753-1760.
[10] 吕谷来, 李建平, 李锵, 俞利兴, 朱松明, 楼建忠, 袁祎琳. 基于机器视觉的砧木定位识别方法[J]. J4, 2011, 45(10): 1766-1770.
[11] 赖小波,朱世强. 基于互相关信息的非参数变换立体匹配算法[J]. J4, 2011, 45(9): 1636-1642.
[12] 王金德, 寿黎但, 李晓燕, 陈刚. 基于多重分割捆绑特征的目标图像检索[J]. J4, 2011, 45(2): 259-266.
[13] 刘建明, 鲁东明, 葛蓉. 基于全局优化的图像修复及其在GPU上实现[J]. J4, 2011, 45(2): 247-252.
[14] 梁文锋,项志宇. 鲁棒的PTZ摄像机目标跟踪算法[J]. J4, 2011, 45(1): 59-63.
[15] 战江涛,刘强,柴春雷. 基于三维模型与Gabor小波的人脸特征点跟踪方法[J]. J4, 2011, 45(1): 30-36.