In this paper, we propose a shape-based image retrieval technique using salience points to describe shapes. This technique consists of a salience point detector robust to noise, a salience representation using angular relative position and curvature value, invariant to rotation, translation and scaling, and an elastic matching algorithm to analyze the similarity. The proposed technique is robust to noise and presents good performance when dealing with shapes of different class but visually similar. The experiments were made in order to illustrate the performance of the proposed technique. The results show the good performance of our method when comparing with other shape-based methods in the literature.