An improved ACO by neighborhood strategy for color image segmentation

Shih Pang Tseng, Ming Chao Chiang, Chu Sing Yang

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

1 Citation (Scopus)

Abstract

This paper presents an efficient method for speeding up ant colony optimization (ACO) in solving the color image segmentation problem. The proposed method is inspired by the heuristics of image segmentation to reduce the computation time. To evaluate the performance of the proposed method, we applied the method on well-known test images. Our experimental results shows that the proposed method can significantly reduce the computation time about 19% to 45%.

Original languageEnglish
Title of host publicationMobile, Ubiquitous, and Intelligent Computing, MUSIC 2013
PublisherSpringer Verlag
Pages615-620
Number of pages6
ISBN (Print)9783642406744
DOIs
Publication statusPublished - 2014 Jan 1
Event4th International Conference on Mobile, Ubiquitous, and Intelligent Computing, MUSIC 2013 - Gwangju, Korea, Republic of
Duration: 2013 Sep 42013 Sep 6

Publication series

NameLecture Notes in Electrical Engineering
Volume274 LNEE
ISSN (Print)1876-1100
ISSN (Electronic)1876-1119

Other

Other4th International Conference on Mobile, Ubiquitous, and Intelligent Computing, MUSIC 2013
CountryKorea, Republic of
CityGwangju
Period13-09-0413-09-06

All Science Journal Classification (ASJC) codes

  • Industrial and Manufacturing Engineering

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