Abstract
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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Castellano, G., Fanelli, A.M., Torsello, M.A. (2011). Fuzzy Image Labeling by Partially Supervised Shape Clustering. In: König, A., Dengel, A., Hinkelmann, K., Kise, K., Howlett, R.J., Jain, L.C. (eds) Knowlege-Based and Intelligent Information and Engineering Systems. KES 2011. Lecture Notes in Computer Science(), vol 6882. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23863-5_9
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DOI: https://doi.org/10.1007/978-3-642-23863-5_9
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