A Template-Based Shape Representation Technique
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.