The variational approach to shape from shading
Computer Vision, Graphics, and Image Processing
Solving for Colour Constancy using a Constrained Dichromatic Reflection Model
International Journal of Computer Vision
A Variational Framework for Retinex
International Journal of Computer Vision
Is Machine Colour Constancy Good Enough?
ECCV '98 Proceedings of the 5th European Conference on Computer Vision-Volume I - Volume I
Beyond Bags of Features: Spatial Pyramid Matching for Recognizing Natural Scene Categories
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
An Algorithm to Determine the Chromaticity Under Non-uniform Illuminant
ICISP '08 Proceedings of the 3rd international conference on Image and Signal Processing
How does the brain arrive at a color constant descriptor?
BVAI'07 Proceedings of the 2nd international conference on Advances in brain, vision and artificial intelligence
IWANN'11 Proceedings of the 11th international conference on Artificial neural networks conference on Advances in computational intelligence - Volume Part II
A skin detection approach based on the Dempster--Shafer theory of evidence
International Journal of Approximate Reasoning
IEEE Transactions on Image Processing
A real-time neural system for color constancy
IEEE Transactions on Neural Networks
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In this paper we propose a biologically inspired computational model based upon the human visual pathway in order to achieve a feature pair that is robust to changes in scene illumination variation. Here, we draw inspiration from the V4 area in the visual cortex and utilise an approach based upon both, the colour opponency and the spatially opponent centre surround receptive field mechanisms present in the human visual system. We do this making use of an optimisation setting which yields the optimal synaptic strength of the centre-surround neurons based on the colour discrimination for the double-opponent feature pair. This approach greatly reduces the effects of the illuminant in terms of discrimination of perceptually similar colours. We illustrate the utility of our approach for purposes of recognising perceptually similar colours, colour-based object recognition and skin detection under widely varying illumination conditions using bench marked data sets. We also compared our results to those yielded by a number of alternatives.