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Modeling of a stereo vision system using a genetic algorithm based fuzzy linear regression

conference contribution
posted on 2007-01-01, 00:00 authored by H Kho, Chee Peng LimChee Peng Lim, A Abdul, H Abu
In this paper a fuzzy linear regression (FLR) model integrated with a genetic algorithm (GA) is proposed. The proposed GA-FLR model is applied to modeling of a stereo vision system. A set of empirical data from stereo vision object measurement is collected based on the full factorial design technique. Three regression models, namely ordinary least-squares regression (OLS), FLR, and GA-FLR, are developed, and with their performances compared. The results show that the proposed GA-FLR model performs better than OLS and FLR in modeling of a stereo vision system.

History

Event

Malaysia-Japan International Symposium on Advanced Technologies (2007 : Kuala Lumpir)

Pagination

1 - 7

Publisher

[The Conference]

Location

Kuala Lumpur, Malaysia

Place of publication

[Kuala Lumpur, Malaysia]

Start date

2007-11-12

End date

2007-11-15

Language

eng

Publication classification

E1.1 Full written paper - refereed

Title of proceedings

MJISAT 2007 : Proceedings of the 2007 Malaysia-Japan International Symposium on Advanced Technologies

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