DocumentCode
2113130
Title
The Research of SVM Introjecting Fuzzy Theory in Image Affective Recognition
Author
Chen, Junjie ; Zhang, Dawei ; Li, Haifang
Author_Institution
Coll. of Comput. & Software, Taiyuan Univ. of Technol., Taiyuan
fYear
2008
fDate
18-18 Dec. 2008
Firstpage
71
Lastpage
74
Abstract
This paper introduces FSVM, which introjects fuzzy theory to SVM, achieves a classification system which classifies image layer by layer to affective semantic level by FSVM, and proposes one kind of image affective semantics classification method. The difficulty is to establish a mapping from image features to image affective semantics and how to select fitting membership function to test image semantic class. The experimental result shows that the system is simple, fast, effective, and so on, therefore our system is proved to be successful in promoting the image semantic classification to affective semantic level.
Keywords
fuzzy set theory; image classification; support vector machines; SVM introjecting fuzzy theory; fitting membership function; image affective recognition; image affective semantics classification method; Biomedical computing; Biomedical engineering; Educational institutions; Fuzzy systems; Humans; Image recognition; Seminars; Shape; Support vector machine classification; Support vector machines; SVM; affective semantic component; fuzzy theory; image affective recognition; membership;
fLanguage
English
Publisher
ieee
Conference_Titel
Future BioMedical Information Engineering, 2008. FBIE '08. International Seminar on
Conference_Location
Wuhan, Hubei
Print_ISBN
978-0-7695-3561-6
Type
conf
DOI
10.1109/FBIE.2008.69
Filename
5076688
Link To Document