Abstract
In this work we propose an approach based on shape clustering for image retrieval. Firstly, shapes of objects contained into images are represented by means of Fourier descriptors. Then, a fuzzy clustering process is applied to automatically discover a set of shape prototypes representative of a number of semantic categories. The adopted fuzzy clustering algorithm is equipped with a mechanism of partial supervision that enables identification of shape categories by taking advantage of some domain knowledge expressed in terms of a set of labeled shapes. Successively, the derived shape prototypes are exploited in order to retrieve shapes similar to a shape query submitted by a user. The suitability of the proposed approach is shown through an experimental comparison on a benchmark dataset in terms of retrieval accuracy.