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. © 2008 Springer-Verlag Berlin Heidelberg.
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CITATION STYLE
Ebrahim, Y., Ahmed, M., Chau, S. C., & Abdelsalam, W. (2008). A template-based shape representation technique. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5112 LNCS, pp. 497–506). https://doi.org/10.1007/978-3-540-69812-8_49
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