Improving the Hough Transform gathering process for affine transformations

被引：6

作者：

Montiel, E

Aguado, AS ^{[1
]}

Nixon, MS

机构：

[1] Univ Surrey, Dept Elect & Elect Engn, Guildford GU2 7XH, Surrey, England

[2] INRIA Rhone Alpes, ZIRST, IMAGIS, F-38330 Montbonnot St Martin, France

[3] Univ Southampton, Southampton SO17 1BJ, Hants, England

来源：

PATTERN RECOGNITION LETTERS | 2001年 / 22卷 / 09期

关键词：

shape extraction; Hough Transform; shape discrimination; object recognition; geometric invariance; geometric constraints; affine;

D O I：

10.1016/S0167-8655(01)00039-3

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 show that significant wrong evidence can be generated when the Hough Transform (HT) is used to extract arbitrary shapes under rigid transformations. In order to reduce the amount of wrong evidence, we consider two types of constraints. First, we define constraints by considering invariant features. Secondly, we consider constraints defined via gradient direction information. Our results show that these constraints can significantly improve the gathering strategy, leading to identification of the correct parameters. The presented formulation is valid for any rigid transformations represented by affine mappings. (C) 2001 Elsevier Science B.V. All rights reserved.

引用

页码：959 / 969

页数：11

共 24 条

[1] On using directional information for parameter space decomposition in ellipse detection [J].