Spectral filter optimization for the recovery of parameters which describe human skin

The 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 i...

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Bibliographic Details
Published in:IEEE transactions on pattern analysis and machine intelligence 2004-07, Vol.26 (7), p.913-922
Main Authors: Preece, S.J., Claridge, E.
Format: Article
Language:English
Subjects:
Algorithms
Application software
Artificial Intelligence
Biomedical imaging
Color
Colorimetry - methods
Computer graphics
Dermoscopy - methods
Humans
image analysis
Image color analysis
Image Enhancement - methods
Image Interpretation, Computer-Assisted - methods
Image reconstruction
medical imaging
Optical filters
optimization
Optimization methods
Pattern Recognition, Automated - methods
Pigmentation
Skin
skin color
Skin Physiological Phenomena
spectral filters
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Description
Summary:The 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.
ISSN:0162-8828
1939-3539
DOI:10.1109/TPAMI.2004.36