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.

引用

页码：497 / +

页数：2

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