An unsupervised generalized Hough transform for natural shapes

被引：10
|
作者：
Bonnet, N [1 ]
机构：
[1] Univ Reims, Hop Maison Blanche, LERI, IFR 53,INSERM,U514,UMRS, F-51092 Reims, France
来源：
PATTERN RECOGNITION | 2002年 / 35卷 / 05期
关键词：
Hough transform; natural shapes; mathematical morphology;
D O I：
10.1016/S0031-3203(01)00219-9
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The Hough transform was originally designed to recognize artifical objects in images. A Hough transform for natural shapes (HTNS) was subsequently proposed, but necessitates the supervised learning of the class of shapes. Here, we extend HTNS to unsupervised pattern recognition, the variability of the object class being coded with tools originating from mathematical morphology (erosion, dilation and distance functions). (C) 2002 Pattern Recognition Society. Published by Elsevier Science Ltd. All rights reserved.
引用
收藏
页码：1193 / 1196
页数：4
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