A Template-Based Shape Representation Technique

Authors:
Yasser Ebrahim;Maher Ahmed;Siu-Cheung Chau;Wegdan Abdelsalam
Affiliations:
Wilfrid Laurier University, Waterloo, Canada N2L 3C5;Wilfrid Laurier University, Waterloo, Canada N2L 3C5;Wilfrid Laurier University, Waterloo, Canada N2L 3C5;University of Guelph, Guelph, Canada N1G 2W1
Venue:
ICIAR '08 Proceedings of the 5th international conference on Image Analysis and Recognition
Year:
2008

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Abstract

In this paper we present a novel approach to shape representation based on correlating a set of object Regions of Interest (RoI) with a set of shape templates. The resultant correlations are the shape features used to build a Template-based Shape Feature Vector (TSFV) that represents the shape of the object. For each class of objects, a set of Main Shape Features (MSFs) is determined so that only the most descriptive features are used when comparing shapes. The proposed technique is tested on two benchmark databases, Kimia-99 and Kimia-216 and is shown to produce competitive results.