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Genetic parameter tuning for reliable segmentation of colored visual tags

  • University of Cape Town

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

This paper reports on a case study on segmentation of colored visual tags for object identification. Lighting variations result in uncertainty in color thresholds leading to unreliable overall system behavior. We describe an experiment with a genetic algorithm (GA) approach for generating reliable thresholds for color identification. We compare it with a maximum distance (MD) approach, and demonstrate that the genetic approach is far more accurate and reliable.

Original languageEnglish
Title of host publicationProceedings of GECCO 2007
Subtitle of host publicationGenetic and Evolutionary Computation Conference
Pages1525
Number of pages1
DOIs
StatePublished - 2007
Event9th Annual Genetic and Evolutionary Computation Conference, GECCO 2007 - London, United Kingdom
Duration: Jul 7 2007Jul 11 2007

Publication series

NameProceedings of GECCO 2007: Genetic and Evolutionary Computation Conference

Conference

Conference9th Annual Genetic and Evolutionary Computation Conference, GECCO 2007
Country/TerritoryUnited Kingdom
CityLondon
Period07/7/0707/11/07

Keywords

  • Color segmentation
  • Genetic algorithms
  • Parameter approximation
  • Visual tags

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