Fuzzy Image Labeling by Partially Supervised Shape Clustering

In this paper, a fuzzy shape annotation approach for automatic image labeling is presented. A fuzzy clustering process guided by partial supervision is applied to shapes represented by Fourier descriptors in order to derive a set of shape prototypes representative of a number of semantic categories. Next, prototypes are manually annotated by attaching textual labels related to semantic categories. Based on the labeled prototypes, a new shape is automatically labeled by associating a fuzzy set that provides membership degrees of the shape to all semantic categories. Experimental results are provided in order to show the suitability of the proposed approach.

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