计算机工程 ›› 2012, Vol. 38 ›› Issue (9): 170-173.doi: 10.3969/j.issn.1000-3428.2012.09.051

• 人工智能及识别技术 • 上一篇    下一篇

大鱼际掌纹识别系统设计与实现

白秋菊1,周兆山2,朱习军1   

  1. (1. 青岛科技大学信息科学技术学院,山东 青岛 266061;2. 青岛市海慈医疗集团,山东 青岛 266033)
  • 收稿日期:2011-10-11 出版日期:2012-05-05 发布日期:2012-05-05
  • 作者简介:白秋菊(1987-),女,硕士研究生,主研方向:图像处理;周兆山,主任医师、博士生导师;朱习军,副教授、博士
  • 基金项目:
    国家自然科学基金资助项目“大鱼际掌纹特应征与5个哮喘易感基因单核苷酸多态性的关联分析”(30873315);山东省自然科学基金资助项目(ZR2009GM007);山东省高校科技计划基金资助项目(J09LG12);青岛市卫生局科技计划基金资助项目(2009-zyz001)

Design and Implementation of Thenar Palmprint Recognition System

BAI Qiu-ju   1, ZHOU Zhao-shan   2, ZHU Xi-jun   1   

  1. (1. College of Information Science and Technology, Qingdao University of Science and Technology, Qingdao 266061, China; 2. Qingdao Hiser Medical Group, Qingdao 266033, China)
  • Received:2011-10-11 Online:2012-05-05 Published:2012-05-05

摘要: 开发一种大鱼际掌纹识别系统。该系统以大鱼际掌纹在变态反应性疾病医学诊断中特应征4级分类为依据。主要功能是在采集到掌纹源图像的情况下,能快速地给出掌纹图像中大鱼际掌纹区域所属的级别,即大鱼际掌纹量化识别,以达到辅助临床医学专家进行诊断的目的,分级采用基于灰度共生矩阵和支持向量机的分类方法。测试结果表明,该系统可以实现大鱼际掌纹的特征提取和分类,精度和效果基本满足医学辅助诊断和研究的要求。

关键词: 大鱼际掌纹, 分类, 灰度共生矩阵, 支持向量机, 纹理

Abstract: This paper designs a thenar palmprint recognition system. In the diagnosis of allergic diseases, thenar palmprint can be divided into four grades based on its special candidates. This system is developed mainly depend on the above, and its main function is able to show the grade of the thenar palmprint quickly in the case of the palm picture is given, and in order to achieve the purpose of supporting clinical experts to diagnose. The classification of Gray Level Co-occurrence Matrix(GLCM) and SVM are used in this system to realize the systematic. Test results show that this system can realize the feature extraction and classification of thenar palmprint, and the precision and effect can make demand of medical aid diagnosis and research.

Key words: thenar palmprint, classification, Gray Level Co-occurrence Matrix(GLCM), Support Vector Machine(SVM), texture

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