An image processing analysis of skin textures

BACKGROUND This paper discusses an image-processing method applied to skin texture analysis. Considering that the characterisation of human skin texture is a task approached only recently by image processing, our goal is to lay out the benefits of this technique for quantitative evaluations of skin features and localisation of defects. METHODS We propose a method based on a statistical approach to image pattern recognition. The results of our statistical calculations on the grey-tone distributions of the images are proposed in specific diagrams, the coherence length diagrams. RESULTS Using the coherence length diagrams, we were able to determine grain size and anisotropy of skin textures. Maps showing the localisation of defects are also proposed. CONCLUSION According to the chosen statistical parameters of grey-tone distribution, several procedures to defect detection can be proposed. Here, we follow a comparison of the local coherence lengths with their average values. More sophisticated procedures, suggested by clinical experience, can be used to improve the image processing.