Clothes Image Searching System Based on CTS

Author

Yi, Ouyang ; Sanyuan, Zhang

Author_Institution

CGIM Lab. of Comput. Sci., Zhejiang Univ., Hangzhou

fYear

2009

fDate

27-28 Feb. 2009

Firstpage

35

Lastpage

39

Abstract

One of the main difficulties in Clothes image searching is the variability of appearance of an object of interest. Clothes image feature extraction is a very active research area under this situation. Through build a Clothes concept semantic structure Clothes Tree Semantic Structure, the Clothes Image Searching System based on Scale Invariant Feature Transform(SIFT) is proposed in the paper. Experiment on an image database of about 5,000 general-purpose images, results show that our algorithm is more efficient than existing algorithms based on color histogram or corners features.

Keywords

clothing; feature extraction; image retrieval; semantic Web; transforms; tree searching; clothes image search system; clothes tree semantic structure; feature extraction; scale invariant feature transform; Clustering algorithms; Communication system software; Computer science; Educational institutions; Feature extraction; Histograms; Image databases; Image retrieval; Laboratories; Spatial databases; CBIR; Clothes; Image features; Semantic;

fLanguage

English

Publisher

ieee

Conference_Titel

Communication Software and Networks, 2009. ICCSN '09. International Conference on

Conference_Location

Macau

Print_ISBN

978-0-7695-3522-7

Type

conf

DOI

10.1109/ICCSN.2009.34

Filename

5076806