Chromaticity space for illuminant invariant recognition

Sivalogeswaran Ratnasingam*, T. Martin McGinnity

*Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    17 Citations (Scopus)

    Abstract

    In this paper, an algorithm is proposed to extract two illuminant invariant chromaticity features from three image sensor responses. The algorithm extracts these chromaticity features at pixel level and therefore can perform well in scenes illuminated with nonuniform illuminant. An approach is proposed to use the algorithm with cameras of unknown sensitivity. The algorithm was tested for separability of perceptually similar colors under the International Commission on Illumination standard illuminants and obtained a good performance. It was also tested for color-based object recognition by illuminating objects with typical indoor illuminants and obtained a better performance compared to other existing algorithms investigated in this paper. 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 color spaces. Based on the results presented, the proposed illuminant invariant chromaticity space can be used for machine vision applications including illuminant invariant color-based object recognition and skin detection.

    Original languageEnglish
    Article number6177664
    Pages (from-to)3612-3623
    Number of pages12
    JournalIEEE Transactions on Image Processing
    Volume21
    Issue number8
    DOIs
    Publication statusPublished - 2012

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