Image Preprocessing Techniques in Skin Diseases Prediction using Deep Learning: A Review

Skin diseases are one of the most common illnesses in human beings worldwide. The early detection of skin diseases becomes important venture to reduce diseases mortality, transmission and improvement. The commonly used methods for skin diseases prediction are Image Processing, Machine Learning, Deep Learning. Among them, now a day's deep learning methods are most common in skin disease prediction. The first step in skin disease prediction using deep learning is image preprocessing. This step plays an important role in diseases prediction because excellent image quality can increase the deep learning models generalization capability. Data cleaning and data conversion are two types of image preprocessing methods. Several methods for image preprocessing have already been proposed by researchers, and various works are also progressing in this field. Each technique has its very own advantages and disadvantages. This study reviews various image preprocessing techniques existing for the identification of skin diseases prediction using deep learning techniques.