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.