Acne detection, assessment, grading and classification using machine learning techniques: a review


Acne is one of the most common problems faced by huge population (above 90%) at different age groups, genders and different area of acne and its severity. Among all acne types, acne vulgaris is most common of them. Acne vulgaris has become an interesting domain for researchers in biomedical engineering as well as image processing. Recognizing acne region and skin areas accurately is really challenging task.This plays a major role in acne detection, grading, classification, acne severity detection and automatic acne assessment. This paper presents a comprehensive review which aim to fill the research gap in literature by providing all the state-of-the-art methods applied till date on acne vulgaris images. This research area is least explored and hence this paper focuses on survey of various image processing and machine learning techniques applied on acne images. Future scope and the problems identified in this domain are also elaborated.

Keywords: – Acne Vulgaris, CNN, Deep learning, Machine learning and Image processing.

Pooja Dhakad1, Sandeep K. Tiwari2*