An efficient segmentation technique for known touching objects using a genetic algorithm approach

Authors:
Edgar Scavino;Dzuraidah Abdul Wahab;Hassan Basri;Mohd Marzuki Mustafa;Aini Hussain
Affiliations:
Faculty of Engineering, Universiti Kebangsaan Malaysia, Selangor DE, Malaysia;Faculty of Engineering, Universiti Kebangsaan Malaysia, Selangor DE, Malaysia;Faculty of Engineering, Universiti Kebangsaan Malaysia, Selangor DE, Malaysia;Faculty of Engineering, Universiti Kebangsaan Malaysia, Selangor DE, Malaysia;Faculty of Engineering, Universiti Kebangsaan Malaysia, Selangor DE, Malaysia
Venue:
AI'07 Proceedings of the 20th Australian joint conference on Advances in artificial intelligence
Year:
2007

Citing 3
Cited 1

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A genetic algorithm for the identification and segmentation of known motion-blurred objects

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Abstract

This paper presents a genetic algorithm (GA) based segmentation technique that can separate two touching objects intended for an automatic recognition of plastic bottles moving on a conveyor belt. The proposed method is based on the possibility to separate the two objects by means of a straight line, whose position is determined by a GA. Extensive testing shows that the proposed method is fast and yields high success rate of correct segmentation with only a limited number of both chromosomes and iterations.