Detection of skin wrinkles and quantification of roughness using a novel image processing technique from a dermatoscope device

OBJECTIVE: Cutaneous relief analysis is crucial in the development of new skincare products, as well as in the evaluation of dermatological treatments. The analysis can be performed by qualitative or quantitative methods. We propose a new algorithm to detect wrinkles and quantify skin roughness by image processing from a dermatoscope. METHODS: A clinical study was carried out with 33 research participants, and images were collected with the dermatoscope and PRIMOS equipment for wrinkle evaluation at two different times: Day 0 (D0) and 45 days (D45) after the use of a dermocosmetic product. Later, a new algorithm was developed to detect wrinkles in the acquired images by applying filters and image transformations that generate a segmented image highlighting the wrinkles. A roughness calculation method is proposed from the pixels belonging to wrinkles. RESULTS: Correlation between the values obtained by the PRIMOS equipment and the proposed system was verified. No correlation was found for data obtained at D0; however, there was correlation at time D45 by Spearman's similarity coefficient. By comparing roughness between times D0 and D45, the treatment was statistically significant for both PRIMOS and the proposed methodology data. CONCLUSION: The wrinkle detection algorithm, in addition to the roughness calculation, demonstrated a sensitivity comparable to the PRIMOS system in evaluating the effectiveness of the dermocosmetic treatment. SIGNIFICANCE: Considering the simplicity of the dermatoscope design compared to other established devices such as PRIMOS, the proposed system is promising as an alternative for dermatological evaluations.