Skin Disease Detection

Abstract

The fundamental objective of this project is to design a prototype system which can be used to detect skin diseases that are Acne detection, Scabies detection, Melanoma detection, Nevus detection, Seborrheic keratosis. This paper focuses on improving the image processing techniques to increase the quality of image and neural network techniques to organize the skin diseases listed above. The blueprint is based on TensorFlow which is mainly used for classification, perception, prediction and creation since it is an open source artificial intelligence library and retraining image classifier using complex neural network. The prototype has been experimented on four variety of skin diseases. When a sample test image is given to prototype, the image will be tested using old trained complex network model. As a result, by implementing this technique skin diseases are recognized with up to 99.52 percent accuracy rates. This prototype has the capability of further improvement in the future. This project has an API endpoint which is the point of entry in a communication channel. When two systems are interacting for Android application and IOS it can be used very methodically by sharing skin diseases’ images. This project has another objective which is to deliver as much information as possible regarding skin diseases detection with this prototype to the general public.