Fingerprint Classification Method Based on Least Square Support Vector Machine and Detailed Image

摘要：

A new online fingerprint identification method is proposed based on detailed image feature and Least-Square Support Vector Machines which has the fast calculate and better generalization capability. This algorithm uses binary tree theory to decompose the problem into three 2-class classification problem, utilizing improved indexing table thinning feature extraction algorithm, then using the support vector machine to optimize the three hyper-planes. Experimental results show that this algorithm improves the efficiency of fingerprint classification.

关键词： Least Square Support Vector Machines Generalization capability Binary tree theory Fingerprint classification

作者: Wang Xianfang Zheng Zhulin Zhang Haiyan

作者单位: Henan Institute of Science and Technology, Xinxiang 453003, China School of Communication and Contro Henan Institute of Science and Technology, Xinxiang 453003, China

会议类型: 国际会议

会议名称: 2009年中国控制与决策会议(2009 Chinese Control and Decision Conference)

会议地点: 广西桂林

会议语种:英文

页码: 3919-3923

在线出版日期: 2009-06-17（万方平台首次上网日期，不代表论文的发表时间）