A content-based image retrieval system based on object-moment feature

Abstract

The last decade has witnessed great interest in research on content-based image retrieval (CBIR). In 2009, Lin et al. proposed a smart CBIR system based on colour and texture feature. Their system has a high detection rate except the cases where image objects have similar shapes. To enhance the detection rate a shape-based image feature called object-moment is proposed in this paper. Object-moment uses the moment of force to compute the object edge feature by calculating the distance from each edge pixel to the axis, and adding them up as a feature. Besides, we integrate the colour features (NSOM, CSOM) and the texture features (CCM, DBPSP) to enhance image detection rate and simplify computation of image retrieval. A series of analyses and comparisons are performed in our experiments to demonstrate that our proposed method improves the retrieval accuracy significantly.

Keywords:

• Content-based image retrieval
• Texture feature
• Edge feature

Acknowledgements

This work was supported in part by National Science Council under the grants NSC 99-2410-H-025-010-MY2 and NSC 101-2410-H-025 -009 -MY2.