![](/images/graphics-bg.png)
A Fuzzy Kernel Maximum Margin Criterion for Image Feature Extraction
Author
Source
Mathematical Problems in Engineering
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-04-14
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Abstract EN
Based on kernel principal component analysis, fuzzy set theory, and maximum margin criterion, a novel image feature extraction and recognition method, called fuzzy kernel maximum margin criterion (FKMMC), is proposed.
In the proposed method, two new fuzzy scatter matrixes are redefined.
The new fuzzy scatter matrix can reflect fully the relation between fuzzy membership degree and the offset of the training sample to subclass center.
Besides, a concise reliable computational method of the fuzzy between-class scatter matrix is provided.
Experimental results on four face databases (AR, extended Yale B, GTFD, and FERET) demonstrate that the proposed method outperforms other methods.
American Psychological Association (APA)
Xuan, Shibin. 2015. A Fuzzy Kernel Maximum Margin Criterion for Image Feature Extraction. Mathematical Problems in Engineering،Vol. 2015, no. 2015, pp.1-13.
https://search.emarefa.net/detail/BIM-1074370
Modern Language Association (MLA)
Xuan, Shibin. A Fuzzy Kernel Maximum Margin Criterion for Image Feature Extraction. Mathematical Problems in Engineering No. 2015 (2015), pp.1-13.
https://search.emarefa.net/detail/BIM-1074370
American Medical Association (AMA)
Xuan, Shibin. A Fuzzy Kernel Maximum Margin Criterion for Image Feature Extraction. Mathematical Problems in Engineering. 2015. Vol. 2015, no. 2015, pp.1-13.
https://search.emarefa.net/detail/BIM-1074370
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1074370