Genetic algorithm with competitive image labelling and least square

被引：14

作者：

Yuen, SY ^{[1
]}

Ma, CH ^{[1
]}

机构：

[1] City Univ Hong Kong, Dept Elect Engn, Kowloon Tong, Hong Kong, Peoples R China

来源：

PATTERN RECOGNITION | 2000年 / 33卷 / 12期

关键词：

genetic algorithm; object recognition; affine template matching; object location and localization; multi-modal optimization; niche model; competition; image labelling; repeated least square; sharing;

D O I：

10.1016/S0031-3203(99)00189-2

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

A multi-modal genetic algorithm using a dynamic population concept is introduced. Each image point is assigned a label and for a chromosome to survive, it must have at least one image point with its label. In this way, the genetic algorithm dynamically segments the scene into one or more objects and the background noise. A Repeated Least Square technique is applied to enhance the convergence performance. The integrated algorithm is tested using a 6 degrees of freedom template matching problem, and it is applied to some images that are challenging for genetic algorithm applications. (C) 2000 Pattern Recognition Society. Published by Elsevier Science Ltd. All rights reserved.

引用

页码：1949 / 1966

页数：18

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