Abstract
This paper presents an application of a Fuzzy Colour Contrast Fusion (FFCF) algorithm in compensating for reduced colour depth representation of a colour image while maintaining efficient colour sensitivity that suffices for accurate real-time colour-based object recognition. We investigate the effects of applying fuzzy colour contrast rules to varying colour depth as we extract the optimal rule combination. The experiments were performed using the robot soccer game set-up with spatially varying illumination intensities on the scene. Interestingly, our results show that for most cases, colour depth reduction could actually improve colour classification via a pie-slice technique, in a modified rg-chromaticity colour space. For 6 different colours, the algorithm was able to yield 6.5% higher overall accuracy with only one-twelfth of LUT size than the full colour depth LUT.
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© 2009 Springer-Verlag Berlin Heidelberg
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Shin, H., Reyes, N.H. (2009). Variable Colour Depth Look-Up Table Based on Fuzzy Colour Processing. In: Köppen, M., Kasabov, N., Coghill, G. (eds) Advances in Neuro-Information Processing. ICONIP 2008. Lecture Notes in Computer Science, vol 5506. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02490-0_130
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DOI: https://doi.org/10.1007/978-3-642-02490-0_130
Publisher Name: Springer, Berlin, Heidelberg
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