Segmentation of Skin Lesion from Digital Images Using Morphological Filter

---------------------------------------------------------------------***--------------------------------------------------------------------Abstract Skin cancer is the deadliest form of skin disease. Its incidence has been rising at a rate of 3% per year. In order to reduce the cost of screening, there is a need for an automated melanoma screening system. Segmentation is significant to detect skin lesion from images. In the proposed method, a novel texture based skin lesion segmentation algorithm is used and probabilistic neural network is used to classify the stages of skin cancer. The feature of the image is extracted by using GLCM algorithm and its features gives better classification with probabilistic neural network. The five different skin lesion is commonly grouped into Basal Cell Carcinoma (BCC), Actinic Keratosis (AK), Squamous Cell Carcinoma (SCC), Melanocytic nevus/mole (MC), Seborrhoeic Keratosis (SK).The system will be used to classify the queried images automatically to choose the stages of abnormality. The morphological filter segmentation is used to detect the skin cancer. The proposed system has higher accuracy, sensitivity, specificity, segmentation compared to other systems.