Resiliency and robustness of alternative shape-based image retrieval techniques

Shape of art object is an important feature for image and multimedia similarity retrievals. However as a consequence of uncertainty shape representation techniques may sometimes work well only in certain environments, and their performance map depend crucially on the quality of the technique used to represent shapes. In this study we focus on shape-based object retrieval under various uncertainty scenarios and conduct a comparison study on four techniques. We measure the effectiveness of the similarity retrieval of the four different shape representation methods (in terms of recall and precision) under the following situations: 1) in the presence of noise in the database, 2) when the exact corner points are unknown, 3)factoring in the human perception on similarity. Our results show, that the similarity retrieval accuracy of our method (MBC-TPV-AS) is better than that of the other methods under uncertainty and discrepancies.