纺织高校基础科学学报Issue(1)：108-115,8.DOI:10.13338/j.issn.1006-8341.2015.01.022
改进的支持向量机算法在人脸识别上的应用
Application of the improved SVM algorithm on face recognition
摘要
Abstract
As a new machine learning method ,support vector machine algorithm has many obvi‐ous advantages in solving the problem of small samples .However ,it is important to select an optimal kernel function and parameters in order to enhance the performance of support vector machine algorithm .In this paper ,the support vector machine algorithm based on hybrid kernel and PSO is proposed by the mixed kernel function method combined with global kernel function and local kernel function ,and after the classification test on the ORL face database ,the results show that the improved algorithm is superior to standard SVM on recognition accuracy .关键词
支持向量机/混合核函数/粒子群优化算法/人脸识别Key words
support vector machine/hybrid kernel function/particle swarm optimized algo-rithm/face recognition分类
数理科学引用本文复制引用
谌璐,贺兴时..改进的支持向量机算法在人脸识别上的应用[J].纺织高校基础科学学报,2015,(1):108-115,8.基金项目
陕西省软科学基金资助项目（2012KRM58）；陕西省教育厅自然科学基金资助项目（12JK0744）；宝鸡文理学院校级重点项目 （）
