Abstract
We present our latest research on skin characterizations by using Contact Capacitive Imaging and High-Resolution Ultrasound Imaging with Machine Learning algorithms. Contact Capacitive Imaging is a novel imaging technology based on the dielectric constant measurement principle, with which we have studied the skin water content of different skin sites and performed image classification by using pre-trained Deep Learning Neural Networks through Transfer Learning. The results show lips and nose have the lowest water content, whilst cheek, eye corner and under-eye have the highest water content. The classification yields up to 83.8% accuracy. High-Resolution Ultrasound Imaging is a state-of-the-art ultrasound technology, and can produce high-resolution images of the skin and superficial soft tissue to a vertical resolution of about 40 microns, with which we have studied the thickness of different skin layers, such as stratum corneum, epidermis and dermis, around different locations on the face and around different body parts. The results show the chin has the highest stratum corneum thickness, and the arm has the lowest stratum corneum thickness. We have also developed two feature-based image classification methods which yield promising results. The outcomes of this study could provide valuable guidelines for cosmetic/medical research, and methods developed in this study can also be extended for studying damaged skin or skin diseases. The combination of Contact Capacitive Imaging and High-Resolution Ultrasound Imaging could be a powerful tool for skin studies.
Highlights
Skin analysis, of facial skin, is very important in many cosmetic and medical applications
We present our latest research on skin characterizations by two novel skin imaging technologies—i.e., Contact Capacitive Imaging and HighResolution Ultrasound Imaging
Skin Contact Capacitive Imaging is a promising, novel imaging technique based on the dielectric constant measurement principle, which has been used for skin water content measurements, and for solvent penetration measurements [6], skin texture/microrelief and hair water content measurements [7,8]
Summary
Of facial skin, is very important in many cosmetic and medical applications. The aim is to measure the skin water content and skin layer thickness of different skin sites, mainly for facial skin, and to perform skin image analysis by using Machine Learning Algorithms. Contact Capacitive Imaging is a novel imaging technique based on the dielectric constant measurement principle. It was originally developed for biometric applications, and has found applications for skin water content as well as skin texture measurements [1,2,3,4,5]. Our previous studies show that with Contact Capacitive Imaging we can analyze skin water content, skin solvent penetrations, skin texture and skin micro-relief analysis [6,7,8,9]
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