Image thresholding using ant colony optimization

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This study is an investigation of the application of ant colony optimization to image thresholding. This paper presents an approach where one ant is assigned to each pixel of an image and then moves around the image seeking low grayscale regions. Experimental results demonstrate that the proposed ant-based method performs better than other two established thresholding algorithms. Further work must be conducted to optimize the algorithm parameters, improve the analysis of the pheromone data and reduce computation time. However, the study indicates that an ant-based approach has the potential of becoming an established image thresholding technique.

Original languageEnglish (US)
Title of host publicationProceedings - Thirteenth International Symposium on Temporal Representation and Reasoning, TIME 2006
DOIs
StatePublished - 2006
Event3rd Canadian Conference on Computer and Robot Vision, CRV 2006 - Quebec City, QC, Canada
Duration: Jun 7 2006Jun 9 2006

Publication series

NameThird Canadian Conference on Computer and Robot Vision, CRV 2006
Volume2006

Conference

Conference3rd Canadian Conference on Computer and Robot Vision, CRV 2006
Country/TerritoryCanada
CityQuebec City, QC
Period6/7/066/9/06

ASJC Scopus subject areas

  • Engineering(all)

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