A novel matrix norm based Gaussian kernel for feature extraction of images

被引：0
|
作者：
Li, Jun-Bao [1 ]
Chu, Shu-Chuan [2 ]
Pan, Jeng-Shyang [3 ]
Ho, Jiun-Huei [4 ]
机构：
[1] Harbin Inst Technol, Dept Automat Test & Control, Harbin 150006, Peoples R China
[2] Cheng Shiu Univ, Dept Informat Management, Chengdu, Peoples R China
[3] Natl Kaohsiung Univ Appl Sci, Dept Elect Engn, Kaohsiung 80778, Taiwan
[4] Cheng Shiu Univ, Dept Elect Engn, Chengdu, Peoples R China
来源：
IIH-MSP: 2006 INTERNATIONAL CONFERENCE ON INTELLIGENT INFORMATION HIDING AND MULTIMEDIA SIGNAL PROCESSING, PROCEEDINGS | 2006年
关键词：
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Gaussian kernel is widely used in Support Vector Machines and many other kernel methods, and it is most often deemed to provide a local measure of similarity between vectors, which causes large storage requirements and large computational effort for transforming images to vectors owing to its viewing images as vectors. A novel matrix norm based Gaussian kernel (M-Gaussian kernel) which views images as matrices is proposed to solve the problem. Experiments conducted on ORL face database show the effectiveness of the proposed M-Gaussian kernel.
引用
收藏
页码：305 / +
页数：2
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