As society develops, many aspects of life are concerned by people, including facial skincare, avoiding acne-related diseases. In this work, we will propose a complete solution for treating acne at home, including 4 processors. First, the anomaly detector uses image processing techniques by Multi-Threshold and Color Segmentation, depending on each color channel corresponding to each type of acne. The sensitivity of the detector is 89.4%. Second, the set of anomalies classifiers into 6 main categories, including 4 major acne types and 2 non-acne types. By applying the convolutional neural model, the accuracy, sensitivity, and F1 are 84.17%, 81.5%, and 82%, respectively. Third, the acne status assessment kit is based on the mGAGS method to classify the condition of a face as mild, moderate, severe, or very severe with an accuracy of 81.25%. Finally, the product recommender, which generalizes from the results of the previous processors with an accuracy of 70-90%. This is the premise that helps doctors as well as general users to evaluate the level of acne on a face effectively and save time.
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