Chromaticity Space for Illuminant Invariant Recognition

In this paper an algorithm is proposed to extract two illuminant invariant chromaticity features from three image sensor responses. This algorithm extracts these chromaticity features at pixel level therefore it can work well in scenes illuminated with non-uniform illuminant. An approach is proposed to use the algorithm with cameras of unknown sensitivity functions. The algorithm was tested for separability of perceptually similar colours under International Commission on Illumination (CIE) standard illuminants and obtained a good performance. The algorithm was also tested for colour based object recognition by illuminating typical indoor illuminants. The proposed algorithm gives a better performance compared to other existing algorithms investigated. Finally, the algorithm was tested for skin detection invariant to illuminant, ethnic background and imaging device. In this investigation daylight scenes under different weather conditions and scenes illuminated by typical indoor illuminants were used. The proposed algorithm gives a better skin detection performance compared to widely used standard colour spaces. Based on the results presented, the proposed illuminant invariant chromaticity space can be used for machine vision applications including illuminant invariant colour based object recognition and skin detection.