An improvement of skin aging assessment by non-invasive laser speckle effect: A comparative texture analysis

Orun, Ahmet; Şeker, Hüseyin; Goodyer, E. N.; Smith, Geoff; Uslan, Volkan

doi:10.1109/bhi.2014.6864294

Cited by 3 publications

(2 citation statements)

References 11 publications

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“…whereas in our work an alternative skin age prediction process can be accomplished by the application of cellular textural analysis in association with a low-cost laser speckle imaging method specified at the 650nm spectral band region, comprehensive texture analysis and the use of machine learning tools like Bayesian networks (BN) [19] [20] or SVM [17] [18]. Our previous experiments [3][4] [5] demonstrated that such a unified method which comprises the above utilities may be capable of identifying the subtle skin abnormalities such as the early stage of skin moles, skin disorders or skin damages, etc. The different variants of applying this method to analyse skin features only necessitate the re-selection of laser wavelength, power and system geometry, without the need for any substantial change in methodology.…”

Section: Introductionmentioning

confidence: 99%

Texture‐based characterization of subskin features by specified laser speckle effects at λ = 650 nm region for more accurate parametric ‘skin age’ modelling

Orun

Şeker

Uslan

et al. 2016

Intern J of Cosmetic Sci

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Objective: The textural structure of "skin age" related sub-skin 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. Conclusion: 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.

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Section: Introductionmentioning

confidence: 99%

Texture‐based characterization of subskin features by specified laser speckle effects at λ = 650 nm region for more accurate parametric ‘skin age’ modelling

Orun

Şeker

Uslan

et al. 2016

Intern J of Cosmetic Sci

Self Cite

View full text Add to dashboard Cite

show abstract

“…Tanaka et al 11 also reported that the textural analysis of elderly digital skin images can be considered as an appropriate method of determining skin integrity in the elderly. Orun et al 12 have highlighted the ability of a new skin aging assessment technique based on laser-speckle imaging method and image processing techniques like texture analysis and Bayesian networks to detect multi-textural changes that reflect cellular skin aging process. Gao et al 13 proposed a simple method to automatically count a skin texture parameter namely the number of grids by using digital image-processing technology.…”

Section: Introductionmentioning

confidence: 99%

An Analysis of Human Dorsal Hand Skin Texture Using Hyperspectral Imaging Technique for Assessing the Skin Aging Process

2016

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Skin texture has become an important issue in recent research with applications in the cosmetic industry and medicine. In this paper, we analyzed the dependence of skin texture features on wavelength as well as on different parameters (age and gender) of human participants using grey-level co-occurrence matrix and hyperspectral imaging technique for a more accurate quantitative assessment of the aging process. A total of 42 healthy participants (men and women; age range, 20-70 years) was enrolled in this study. A region of interest was selected from the hyperspectral images. The results were analyzed in terms of texture using the gray-level co-occurrence matrix which generated four features (homogeneity, contrast, entropy, and correlation). The results showed that most of these features displayed variations with wavelength (the exception was entropy), with higher variations in women. Only correlation in both sexes and contrast in men proved to vary statistically significant with age, making them the targeted variables in future attempts to characterize aging skin using the complex method of hyperspectral imaging. In conclusion, by using hyperspectral imaging some measure of the degree of damage or the aging process of the hand skin can be obtained, mainly in terms of correlation values. At the present time, reasonable explanations that can link the process of skin aging and the above mentioned features could not be found, but deeper investigations are on the way.

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Prediction of skin ages by means of multi-spectral light sources

Şeker

Uslan

Orun

et al. 2014

2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society

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Assessment of skin aging is a complex biological process that depends on various internal and external factors but has become important due to personalized skin health and cosmetic treatments. Although there are a small number of attempts to assess the skin aging, they identify only one of the previously classified skin aging groups. The methods used to achieve it are also based generally on highly expensive measurement devices. This work therefore proposes novel low-cost skin aging assessment apparatus by using light back-scatter intensity level of Red, Blue, Green and Infrared bands. This is further enhanced by using a machine learning method to accurately predict actual skin age. The proposed method appears to be highly capable of capturing multi-layer cellular changes exhibited by the biological skin aging process and predicting skin ages with a root-mean-square error of as low as 0.160 by using only four features based on the four multi-spectral light sources. This assessment kit seems to be the first of its kind, which is expected to bring great benefit to both personalized skin healthcare and cosmetic sectors.

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An improvement of skin aging assessment by non-invasive laser speckle effect: A comparative texture analysis

Cited by 3 publications

References 11 publications

Texture‐based characterization of subskin features by specified laser speckle effects at λ = 650 nm region for more accurate parametric ‘skin age’ modelling

Texture‐based characterization of subskin features by specified laser speckle effects at λ = 650 nm region for more accurate parametric ‘skin age’ modelling

An Analysis of Human Dorsal Hand Skin Texture Using Hyperspectral Imaging Technique for Assessing the Skin Aging Process

Prediction of skin ages by means of multi-spectral light sources

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