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

SJ Preece, Elzbieta Claridge

Research output: Contribution to journalArticle

36 Citations (Scopus)


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.
Original languageEnglish
Pages (from-to)913-922
Number of pages10
JournalIEEE Transactions on Pattern Analysis and Machine Intelligence
Issue number7
Publication statusPublished - 1 Jan 2004


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