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Genetic parameter tuning for reliable segmentation of colored visual tags

Published: 07 July 2007 Publication History

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.

Reference

[1]
Mbogho, A.J.W. and Scarlatos, L.L. Towards reliable computer vision-based tangible user interfaces. Proceedings of IASTED-HCI 2005 (Nov. 2005), 155--160.

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  1. Genetic parameter tuning for reliable segmentation of colored visual tags

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      cover image ACM Conferences
      GECCO '07: Proceedings of the 9th annual conference on Genetic and evolutionary computation
      July 2007
      2313 pages
      ISBN:9781595936974
      DOI:10.1145/1276958

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      Association for Computing Machinery

      New York, NY, United States

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      Published: 07 July 2007

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      Author Tags

      1. color segmentation
      2. genetic algorithms
      3. parameter approximation
      4. visual tags

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      GECCO '07 Paper Acceptance Rate 266 of 577 submissions, 46%;
      Overall Acceptance Rate 1,669 of 4,410 submissions, 38%

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