학술논문

Spectral filter optimization for the recovery of parameters which describe human skin
Document Type
Periodical
Source
IEEE Transactions on Pattern Analysis and Machine Intelligence IEEE Trans. Pattern Anal. Mach. Intell. Pattern Analysis and Machine Intelligence, IEEE Transactions on. 26(7):913-922 Jul, 2004
Subject
Computing and Processing
Bioengineering
Humans
Skin
Optical filters
Biomedical imaging
Application software
Optimization methods
Image color analysis
Pigmentation
Computer graphics
Image reconstruction
Color
image analysis
spectral filters
optimization
skin color
medical imaging.
Language
ISSN
0162-8828
2160-9292
1939-3539
Abstract
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.