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Titolo:
Genetic algorithm with competitive image labelling and least square
Autore:
Yuen, SY; Ma, CH;
Indirizzi:
City Univ Hong Kong, Dept Elect Engn, Kowloon Tong, Hong Kong, Peoples R China City Univ Hong Kong Kowloon Tong Hong Kong Peoples R China oples R China
Titolo Testata:
PATTERN RECOGNITION
fascicolo: 12, volume: 33, anno: 2000,
pagine: 1949 - 1966
SICI:
0031-3203(200012)33:12<1949:GAWCIL>2.0.ZU;2-9
Fonte:
ISI
Lingua:
ENG
Soggetto:
HOUGH TRANSFORM;
Keywords:
genetic algorithm; object recognition; affine template matching; object location and localization; multi-modal optimization; niche model; competition; image labelling; repeated least square; sharing;
Tipo documento:
Article
Natura:
Periodico
Settore Disciplinare:
Engineering, Computing & Technology
Citazioni:
23
Recensione:
Indirizzi per estratti:
Indirizzo: Yuen, SY City Univ Hong Kong, Dept Elect Engn, 83 Tat Chee Ave, Kowloon Tong, Hong Kong, Peoples R China City Univ Hong Kong 83 Tat Chee Ave Kowloon Tong Hong Kong Peoples R China
Citazione:
S.Y. Yuen e C.H. Ma, "Genetic algorithm with competitive image labelling and least square", PATT RECOG, 33(12), 2000, pp. 1949-1966

Abstract

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 someimages that are challenging for genetic algorithm applications. (C) 2000 Pattern Recognition Society. Published by Elsevier Science Ltd. All rights reserved.

ASDD Area Sistemi Dipartimentali e Documentali, Università di Bologna, Catalogo delle riviste ed altri periodici
Documento generato il 01/06/20 alle ore 12:02:14