An effective method for combining multiple features of image retrieval

We propose an image retrieval system using the Borda count method in combining multiple experts (CME). It combines color-, shape- and texture-based retrieval systems. CME method can complementarily combine results of each retrieval system, which uses different features. There are some problems when the Borda count method in pattern recognition is applied to image retrieval. Thus, we propose a modified Borda count method to solve these problems. In the experiment our method reduces false positive errors and produces better results than that of each retrieval module that uses only one feature.

[1]  James Ze Wang,et al.  Wavelet-based image indexing techniques with partial sketch retrieval capability , 1997, Proceedings of ADL '97 Forum on Research and Technology. Advances in Digital Libraries.

[2]  Shi-Kuo Chang,et al.  Principles of pictorial information systems design , 1988 .

[3]  Ching Y. Suen,et al.  The behavior-knowledge space method for combination of multiple classifiers , 1993, Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.

[4]  Dong-Seok Jeong,et al.  Image indexing technique using entropy measures with a multilevel multiresolution approach , 1997, Electronic Imaging.

[5]  Markus A. Stricker,et al.  Similarity of color images , 1995, Electronic Imaging.