A Survey on Design a Machine Learning Method to Identify Skin Diseases Using Machine Learning and Image Processing

Machine learning algorithms are being used extensively in biomedical fields for segmentation and analysis. These algorithms use features derived from images as input to make a conclusion. So, choosing proper feature extraction methods pooled with suitable Machine Learning (ML) algorithms is very important to accomplish good classification accuracy. During the literature survey, we found that there is a deficiency of information about machine learning algorithms for skin disease classification. Image Processing and machine learning based examinations are being utilized in a few territories; for example, face recognition, unique finger impression recognition, tumor identification and segmentation. Generally used ML algorithms are Linear Differential Analysis (LDA), Support Vector Machine (SVM), Artificial Neural Networks (ANN), Nave Bias Classier, K-Nearest Neighbor (KNN) and Deep Learning Algorithm. The choice of information include is crucial in any classification task, utilizing ML calculations.