Skin Image Processing and Skin Characterizations

PhD Thesis

Pan, W (2017). Skin Image Processing and Skin Characterizations. PhD Thesis London South Bank University School of Engineering
AuthorsPan, W
TypePhD Thesis

The skin hydration and skin Trans epidermal water loss (TEWL) are of great
importance in many skin research areas, such as dermatology, clinical analysis,
pharmacology and cosmetic science etc. However, to measure them is not easy.
Over the year , our research group has developed three novel technologies for such
measurement : Opto Thermal Transient Emission Radiometry (OTTER),
AquaFlux and capacitive contact imaging based on the Fingerprint sensor. The aim
of this research is to develop new skin image processing and data analysis
techniques for capacitive contact images, as well as digital colour images, and to
develop new methodologies for skin characterization by using the three
For skin image processing, a new GUI based MATLAB programme has been
developed, which can be used for extracting and analysing the images from the
result files created by the measurement instruments. The programme implement
the skin image processing techniques such as image enhancement (i.e. brightness
equalization, extraction of skin texture, hair removal), image stitching, image
matching and skin surface 3D profiling etc. Another image processing programme
based on OpenCV has also been developed, which is more suitable for real time
video processing, including contour detection, texture extraction and face
detection etc.
For the skin characterization, several experiments are conducted: skin over
hydration experiments; kin damage assessment including intensive washing, SLS
irritations, and tape stripping; dermabrasion experiments; soap drying effect
assessment. These experiments provide better understandings of the technologies.
The occlusion effects in capacitive images shows good potential for skin damage
assessment, as it can not only reflect the scale of damage, but also the types of

PublisherLondon South Bank University
Digital Object Identifier (DOI)
Publication dates
Print01 Jul 2017
Publication process dates
Deposited23 Feb 2018
Publisher's version
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