The color retrieval system with color component analysis

Author

Choi, Chul ; Choi, Young Kwan ; Park, Chang Choon

Author_Institution

Dept. of Comput. Sci. & Eng., KONKUK Univ., Seoul

fYear

2004

fDate

14-14 May 2004

Firstpage

35

Lastpage

39

Abstract

This paper intends to propose a way of utilizing color components for image retrieval. Like CLCM, GLCM (color, gray level co-occurrence matrix) (R. M. Haralick et al., Nov. 1973) and invariant moment (M.K. Hu, Sep. 1961)(M.K. Hu, Feb. 1962) use 2D distribution chart, which use basic statistical techniques in order to interpret 2D data. In order to interpret the spatial relationship and weight of data, this study has used principal component analysis (G. Pass et al., 1996)(Jun Zhang, Sep. 1997) that is used in multivariate statistics. In order to increase accuracy of data, it has proposed a way to project color components on 3D space, to rotate it and then, to extract features of data from all angles

Keywords

feature extraction; image colour analysis; image retrieval; principal component analysis; statistical distributions; 2D distribution chart; color component analysis; color level cooccurrence matrix; color retrieval system; feature extraction; gray level cooccurrence matrix; image retrieval; multivariate statistics; principal component analysis; statistical technique; Computer science; Data mining; Histograms; Image analysis; Image color analysis; Image processing; Image retrieval; Principal component analysis; Shape measurement; Statistical analysis;

fLanguage

English

Publisher

ieee

Conference_Titel

Imaging Systems and Techniques, 2004. (IST). 2004 IEEE International Workshop on

Conference_Location

Stresa

Print_ISBN

0-7803-8591-8

Type

conf

DOI

10.1109/IST.2004.1397277

Filename

1397277