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。
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.
出处
《计算机工程》
CAS
CSCD
2012年第9期170-173,共4页
Computer Engineering
基金
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)
关键词
大鱼际掌纹
分类
灰度共生矩阵
支持向量机
纹理
thenar palmprint
classification
Gray Level Co-occurrence Matrix（GLCM）
Support Vector Machine（SVM）
texture
