A fuzzy set approach for shape-based image annotation

  • Authors:
  • Giovanna Castellano;Anna Maria Fanelli;Maria Alessandra Torsello

  • Affiliations:
  • CILab - Computational Intelligence Laboratory, Computer Science Department, University of Bari, Bari, Italy;CILab - Computational Intelligence Laboratory, Computer Science Department, University of Bari, Bari, Italy;CILab - Computational Intelligence Laboratory, Computer Science Department, University of Bari, Bari, Italy

  • Venue:
  • WILF'11 Proceedings of the 9th international conference on Fuzzy logic and applications
  • Year:
  • 2011

Quantified Score

Hi-index 0.00

Visualization

Abstract

In this paper, we present a shape labeling approach for automatic image annotation. A fuzzy clustering process is applied to shapes represented by Fourier descriptors in order to derive a set of shape prototypes. Then, prototypes are manually annotated by textual labels corresponding 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 classes. Preliminary results show the suitability of the proposed approach to image annotation by encouraging its application in wider application contexts.