Skin disease prognosis from dermascopic images with image processing and IoT

Abstract

Dermatology is one of the major fields of prescription which is worried about the analysis and treatment of skin disorders. Skin diseases are among the most widely recognized medical issues around the world. Regardless of being common, their determination is quite troublesome and requires broad knowledge and expertise in the area. Skin disease might cause severe health and monetary consequences for patients if not detected and controlled early. Early recognition can forestall the condition from worsening. The proposed work presents the development of an automated skin disease diagnosis system which takes images of a skin disease as an input by the user and predicts the type of skin disease. The system uses a dual stage approach for detection and displaying process which effectively uses image processing and IoT. In the 1st stage, the image of the skin condition is subject to numerous types of pre-processing techniques followed by feature extraction. The extracted features are fed to the SVM classifier to identify disease and predict accordingly. On training and testing for 5 diseases the system produces an overall prediction accuracy of 90%.