Texture-based characterization of subskin features by specified laser speckle effects at λ = 650 nm region for more accurate parametric 'skin age' modelling.
OBJECTIVE
The textural structure of 'skin age'-related subskin components enables us to identify and analyse their unique characteristics, thus making substantial progress towards establishing an accurate skin age model.


METHODS
This is achieved by a two-stage process. First by the application of textural analysis using laser speckle imaging, which is sensitive to textural effects within the λ = 650 nm spectral band region. In the second stage, a Bayesian inference method is used to select attributes from which a predictive model is built.


RESULTS
This technique enables us to contrast different skin age models, such as the laser speckle effect against the more widely used normal light (LED) imaging method, whereby it is shown that our laser speckle-based technique yields better results.


CONCLUSIONS
The method introduced here is non-invasive, low cost and capable of operating in real time; having the potential to compete against high-cost instrumentation such as confocal microscopy or similar imaging devices used for skin age identification purposes.
Faculty of Technology, De Montfort University, Gateway House, Leicester, LE1 9BH, UK.
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Orun
Department of Computer and Information Sciences, University of Northumbria at New Castle, Newcastle, UK.
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Seker
Faculty of Technology, De Montfort University, Gateway House, Leicester, LE1 9BH, UK.
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Uslan
Faculty of Technology, De Montfort University, Gateway House, Leicester, LE1 9BH, UK.
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Goodyer
Leicester School of Pharmacy, Health and Life Sciences, De Montfort University, Gateway, Leicester, LE1 9BH, UK.
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Smith
D000328:Adult; D000367:Age Factors; D001499:Bayes Theorem; D006801:Humans; D007834:Lasers; D008962:Models, Theoretical; D015595:Skin Aging; D013057:Spectrum Analysis / Q000379:methods*; D055815:Young Adult
Bayesian networks; lasers; skin age; texture analysis