Solving for Colour Constancy using a Constrained Dichromatic Reflection Model
International Journal of Computer Vision
IPMI '97 Proceedings of the 15th International Conference on Information Processing in Medical Imaging
Markov-Gibbs random field modeling of 3D skin surface textures for haptic applications
ICCSA'07 Proceedings of the 2007 international conference on Computational science and Its applications - Volume Part II
Model-based parameter recovery from uncalibrated optical images
MICCAI'05 Proceedings of the 8th international conference on Medical image computing and computer-assisted intervention - Volume Part II
Journal of Biomedical Imaging
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This paper presents a method for finding spectral filters that minimize the error associated with histological parameters characterizing normal skin tissue. These parameters can be recovered from digital images of the skin using a physics-based model of skin coloration. The relationship between the image data and histological parameter values is defined as a mapping function from the image space to the parameter space. The accuracy of this function is determined by the choice of optical filters. An optimization criterion for finding the optimal filters is defined by combing methodology from differential geometry with statistical error analysis. It is shown that the magnitude of errors associated with the optimal filters is typically half of that for typical RGB filters on a three-parameter model of human skin coloration. Finally, other medical image applications are identified to which this generic methodology could be applied.