Skin Disease Detection Using Image Processing and Machine Learning
Authors:-Assistant Professor Punashri Patil, Prathvish Shetty, Nikhil Shinde, Ashirwad Swami, Sahil Hanwate
Abstract-Skin diseases affect millions worldwide, making early and accurate diagnosis essential for effective treatment. Traditional diagnostic methods rely on manual visual inspection, which can be subjective and prone to errors due to variations in expertise and environmental factors. Misdiagnosis or delayed treatment can lead to severe complications, especially in conditions like melanoma. This paper presents an automated approach to skin disease detection using image processing and machine learning. The proposed system enhances image quality through preprocessing, extracts crucial features, and classifies skin conditions using algorithms like Support Vector Machine (SVM) and Convolutional Neural Networks (CNN). Experimental results demonstrate high classification accuracy, highlighting AI’s potential in dermatology for faster and more consistent diagnoses. By integrating artificial intelligence into dermatological assessments, this research aims to bridge the gap between conventional diagnosis and AI-assisted solutions, making skin disease detection more accessible, precise, and efficient.
