Adaptive colour calibration for object tracking under spatially-varying illumination environments

Heesang Shin*, Napoleon H. Reyes, Andre L. Barczak

*Corresponding author for this work

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


In the context of a Fuzzy-Genetic system, auto-calibration of colour classifiers, under spatially varying illumination conditions, to produce near perfect object recognition accuracy requires a balancing act for the fitness function. One general approach would be to maximise the true positives while minimising the false positives. This has been found effective in the presence of large amount of noise. However, experiments show that this fitness function needs improvement for cases where there are target colours with similar hues. In this paper, we present an extension to our fuzzy-genetic colour contrast fusion algorithm, now utilising a fitness function that detects clusters of false positives, and limits the search space for finding the properties of the colour classifier. We tested the performance of the auto-calibrated colour classifiers by subjecting them to object recognition tasks in the robot soccer domain, under varying illumination conditions, until we find its limits. It was observed that the accuracy of the object recognition began to degrade, on the average, at illumination settings that are either about three times brighter (starting from 797.4 lux), or two times darker (less than 138 lux) than what it was trained for (average of 285.47 lux). Otherwise, near perfect recognition accuracy is achieved.

Original languageEnglish
Title of host publicationNeural Information Processing - 18th International Conference, ICONIP 2011, Proceedings
EditorsBao-Liang Lu, Liqing Zhang, James Kwok
Number of pages11
Publication statusPublished - 2011
Externally publishedYes
Event18th International Conference on Neural Information Processing, ICONIP 2011 - Shanghai, China
Duration: 13 Nov 201117 Nov 2011
Conference number: 18th

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 3
Volume7064 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference18th International Conference on Neural Information Processing, ICONIP 2011
Abbreviated titleICONIP


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