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2 November 2011 A novel illumination-invariant colour constancy algorithm
L. A. Torres-Méndez, M. L. Quiñones Muñoz, E. J. Olaya-Benítez
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Proceedings Volume 8011, 22nd Congress of the International Commission for Optics: Light for the Development of the World; 80119C (2011) https://doi.org/10.1117/12.901951
Event: International Commission for Optics (ICO 22), 2011, Puebla, Mexico
Abstract
The human brain is able to extract the colour of objects no matter the existing illumination conditions which may affect the appearance of their colour. For a person, an object that is red, it will be red regardless of the type of illumination source. However, for a computer algorithm to achieve the same task is not as simple. For vision and robotics applications were feature extraction is essential having such an algorithm is crucial. It is well known from the literature that the colour of an object does not only depend on the chemical composition and shape of its surface but also on the illumination conditions, the intensity, number, location and colour of the sources of illumination as well as the intrinsic and extrinsic characteristics of the sensor used. Based on that knowledge, we propose a simple colour constancy algorithm that uses the quaternion representation of each pixel in the image instead of the commonly used RGB model. We assume linearity in the reception of the luminance spectrum of the charge-coupled device of the camera before variations in the illumination. We have tested our colour constancy algorithm in a variety of images containing different colour objects under different illumination conditions. Our experimental results show the feasibility of the proposed method.
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L. A. Torres-Méndez, M. L. Quiñones Muñoz, and E. J. Olaya-Benítez "A novel illumination-invariant colour constancy algorithm", Proc. SPIE 8011, 22nd Congress of the International Commission for Optics: Light for the Development of the World, 80119C (2 November 2011); https://doi.org/10.1117/12.901951
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KEYWORDS
RGB color model
Image segmentation
Image processing algorithms and systems
Detection and tracking algorithms
Image visualization
Brain
Charge-coupled devices
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