Abstract
The work presented in this article aims at shape feature extraction and description. In this paper, we propose a shape-based image retrieval technique using salience points to describe shapes. The saliences of a shape are defined as the higher curvature points along the shape contour. The technique presented here consists of: a salience point detector; a salience representation using angular relative position and curvature value analyzed from a multi-scale perspective; and a matching algorithm considering local and global features to calculate the dissimilarity. The proposed technique is robust to noise and presents good performance when dealing with shapes of different classes but visually similar. The experiments were made in order to illustrate the performance of the proposed technique, and the results show the good performance of our method when compared with other shape-based methods in literature.
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