Applying ant colony optimization to binary thresholding

Alice R. Malisia, Hamid R. Tizhoosh

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

Abstract

This paper is an investigation of the application of ant colony optimization to image thresholding. It presents an approach where ants are assigned to each pixel of an image and they move around the image seeking low grayscale regions. The proposed ant-based method performs better than three other established thresholding algorithms. Further work must be conducted to optimize parameters, select the best cost function, improve the analysis of the pheromone data and reduce computation time. The study indicates that an ant-based approach has the potential of becoming an established image thresholding technique.

Original languageEnglish (US)
Title of host publication2006 IEEE International Conference on Image Processing, ICIP 2006 - Proceedings
Pages2409-2412
Number of pages4
DOIs
StatePublished - 2006
Event2006 IEEE International Conference on Image Processing, ICIP 2006 - Atlanta, GA, United States
Duration: Oct 8 2006Oct 11 2006

Publication series

NameProceedings - International Conference on Image Processing, ICIP
ISSN (Print)1522-4880

Other

Other2006 IEEE International Conference on Image Processing, ICIP 2006
Country/TerritoryUnited States
CityAtlanta, GA
Period10/8/0610/11/06

Keywords

  • Image processing
  • Optimization methods

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition
  • Signal Processing

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