Personal identification based on skin texture features from the forearm and multi-modal imaging

The Development of a Skin Image Analysis Tool by Using Machine Learning Algorithms

We present our latest research work on the development of a skin image analysis tool by using machine-learning algorithms. Skin imaging is very import in skin research. Over the years, we have used and developed different types of skin imaging techniques. As the number of skin images and the type of skin images increase, there is a need of a dedicated skin image analysis tool. In this paper, we report the development of such software tool by using the latest MATLAB App Designer. It is simple, user friendly and yet powerful. We intend to make it available on GitHub, so that others can benefit from the software. This is an ongoing project; we are reporting here what we have achieved so far, and more functions will be added to the software in the future.

Micro-relief analysis with skin capacitive imaging

BACKGROUND

In this study, the performance of capacitive imagining in skin micro-relief analysis was investigated. This measurement principle has been used for skin hydration measurements over the last decade and it is commercially available by various manufacturers. Strengthening its potential for new applications could offer an affordable and portable multi-purpose device for in vivo skin research. Previous studies in the literature have used a wide range of optical devices to determine how the skin surface topographic features are affected by chronological age, environmental influences and living habits.

MATERIAL AND METHODS

A capacitive system was used in order to capture hydration images from the middle volar forearm of twelve volunteers. The visual output of the system was studied and image processing algorithms were adapted to automatically extract skin micro-relief features. The change in the skin network of lines during arm extension, the lines' anisotropy index and the number of closed polygons per skin surface area were plotted against the subjects' chronological age. The results were compared with optical measurements from the literature to validate our algorithms and evaluate the capacitive imaging in skin micro-relief analysis.

RESULTS

The change in the intensity of primary and secondary lines during arm extension and the number of closed polygons per surface area were in agreement with the literature. The anisotropy index output gave inconclusive results.

CONCLUSIONS

The experimental results show that the capacitive systems could only extract two-dimensional skin topographic features.