International Journal of Science, Engineering and TechnologyAuthors: Professor Jayachandiran. V,, Sweety Swanthika. M, Yash Mallya, Dr, Dr. Jeya Prabha, A
Abstract: Timely medical intervention and effective treatment rely heavily on the early identification of skin diseases. This project introduces a real-time skin disease recognition system utilizing a live camera on a Raspberry Pi, designed to detect and classify three common skin conditions: Actinic Keratosis, Pigmented Benign Keratosis, and Melanoma. A deep learning model, trained on a diverse dataset of skin images, is deployed on the Raspberry Pi to provide efficient and low-cost diagnosis, capturing and processing live skin images to deliver instant classification results, this system provides 96% accuracy and 58%, 12% and 36% sensitivity for each disease respectively, enabling early detection and facilitating prompt medical consultation, and enhancing accessibility to dermatological analysis, particularly in remote areas.
