Skin Cancer Detection Using Image Processing

Skin cancer poses a significant health concern globally, demanding prompt identification and treatment for favorable patient prognosis.This study introduces an automated system for skin cancer detection through advanced image processing methodologies.Employing algorithms for image analysis and classification, the system distinguishes skin lesions into distinct categories: melanoma, basal cell carcinoma, or normal skin.The implementation of this technology aims to augment diagnostic precision, particularly in regions with limited access to specialized dermatological services.Through the integration of image processing techniques and transfer learning models, this project contributes to early detection strategies, facilitating timely interventions and improved clinical outcomes in skin cancer management.