Fuzzy Shape Clustering for Image Retrieval

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.