Melanoma is the deadliest form of skin cancer. Incidence rates of melanoma have been increasing, especially among non-Hispanic white males and females, but survival rates are high if detected early. Due to the costs for dermatologists to screen every patient, there is a need for an automated system to assess a patient’s risk of melanoma using images of their skin lesions captured using a standard digital camera. One challenge in implementing such a system is locating the skin lesion in the digital image. In Proposed method a novel texture-based skin lesion segmentation algorithm is proposed. And classify the stages of skin cancer using Probabilistic neural network. Because in skin lesions lots of stages are there so probabilistic neural network will give better performance in this system. The proposed framework has higher segmentation accuracy compared to all other tested algorithms.