A study of shape-based image retrieval

Author

Lin, Hwei-Jen ; Kao, Yang-Ta ; Yen, Shwu-Huey ; Wang, Chia-Jen

Author_Institution

Dept. of Comput. Sci. & Inf. Eng., Tamkang Univ., Taipei, Taiwan

fYear

2004

fDate

23-24 March 2004

Firstpage

118

Lastpage

123

Abstract

Content-based image retrieval (CBIR) work includes feature selection, object representation, and matching. If a shape is used as feature, edge detection might be the first step to extract that feature. Invariance to translation, rotation, and scale is required by a good shape representation. Sustaining deformation contour matching is an important issue at the matching process. An efficient and robust shape-based image retrieval system is proposed. We use the Prompt edge detection method [H.J. Lin et al., (2001)] to detect edge points, which is compared with the Sobel edge detection method. We also introduce a shape representation method, the mountain-climbing sequence (MCS), that is invariant to translation, rotation, and scale problems. The results of our proposed method show a superior matching ratio even in the presence of a modest level of deformation.

Keywords

content-based retrieval; edge detection; feature extraction; image matching; image representation; image retrieval; visual databases; Prompt edge detection; Sobel edge detection; content-based image retrieval; deformation contour matching; feature extraction; feature selection; mountain-climbing sequence; object representation; shape representation; shape-based image retrieval; superior matching ratio; Active contours; Computer vision; Content based retrieval; Data mining; Image edge detection; Image retrieval; Information retrieval; Noise shaping; Robustness; Shape;

fLanguage

English

Publisher

ieee

Conference_Titel

Distributed Computing Systems Workshops, 2004. Proceedings. 24th International Conference on

Print_ISBN

0-7695-2087-1

Type

conf

DOI

10.1109/ICDCSW.2004.1284018

Filename

1284018