A New Kernel Function Based Face Recognition Algorithm

摘要：

In general, using kernel function to solve problems of non-linear and recognition ratio, as is done in human face recognition, is particularly effectively. Firstly, a hybrid kernel function is constructed, and then a modified human face recognition algorithm about Kernel-based KICA and Kernel-based improved PSVM methods is presented. The traditional ICA methods have limitations for non-linear image in facial feature extraction process. Using kernel-based non-linear image characteristics, KICA method analyses data in the high-dimensional feature space. As a machine learning algorithm, SVM also has some limitations. This article presents an improved Nonlinear PSVM algorithm to get a better recognition ratio and a little time consuming. Eventually the tests for feasibility are performed.

作者: JingHua Cao YanZhong Ran ZhUun Xu

作者单位: Department of Computer University of Ji Lin lin JiLin Province,China

会议类型: 国际会议

会议名称: 2010 International Conference on Computer,Mechatronics,Control and Electronic Engineering(2010计算机、机电、控制与电子工程国际会议 CMCE 2010)

会议地点: 长春

会议语种:英文

页码: 226-230

在线出版日期: 2010-08-24（万方平台首次上网日期，不代表论文的发表时间）