A template-based shape representation technique

被引：0
|
作者：
Ebrahim, Yasser [1 ]
Ahmed, Maher [1 ]
Chau, Siu-Cheung [1 ]
Abdelsalam, Wegdan [2 ]
机构：
[1] Wilfrid Laurier Univ, Waterloo, ON N2L 3C5, Canada
[2] Univ Guelph, Guelph, ON N1G 2W1, Canada
来源：
IMAGE ANALYSIS AND RECOGNITION, PROCEEDINGS | 2008年 / 5112卷
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
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.
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页码：497 / +
页数：2
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