Content-based image retrieval (CBIR) systems have been developed aiming at enabling users to search and retrieve images based on their properties such as shape, color and texture. We are concerned with shape-based image retrieval. Here, we discuss a recently proposed shape descriptor, called contour saliences, defined as the influence areas of its higher curvature points. We introduce a robust approach to estimate contour saliences by exploiting the relation between a contour and its skeleton, modifies the original definition to include the location and the value of saliences along the contour, and proposes a new metric to compare contour saliences. We also evaluate the effectiveness of the proposed descriptor with respect to Fourier descriptors, curvature scale space and moment invariants.