Shape-based image retrieval using pair-wise candidate co-ranking

Authors:
A. El-ghazal;O. Basir;S. Belkasim
Affiliations:
Electrical and Computer Engineering, University of Waterloo, ON., Canada;Electrical and Computer Engineering, University of Waterloo, ON., Canada;Computer Science, Georgia State University, Atlanta, GA
Venue:
ICIAR'07 Proceedings of the 4th international conference on Image Analysis and Recognition
Year:
2007

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Abstract

Shape-based image retrieval is one of the most challenging aspects in Content-Based Image Retrieval (CBIR). A variety of techniques are reported in the literature that aim to retrieve objects based on their shapes; each of these techniques has its advantages and disadvantages. In this paper, we propose a novel scheme that exploits complementary benefits of several shape-based image retrieval techniques and integrates their assessments based on a pairwise co-ranking process. The proposed scheme can handle any number of CBIR techniques; however, three common techniques are used in this study: Invariant Zernike Moments (IZM), Multi-Triangular Area Representation (MTAR), and Fourier Descriptor (FD). The performance of the proposed scheme is compared with that of each of the selected techniques. As will be demonstrated in this paper, the proposed co-ranking scheme exhibits superior performance.