Abstract: Melanoma, basal cell carcinoma, and squamous cell carcinoma are among the different forms of skin cancers. Melanoma is the most unstable of the melanomas. One of the most serious diseases in humans is malignant melanoma. Doctors can be able to treat patients if they are diagnosed early. Computer vision plays an important role in medical image diagnosis. The identification of melanoma skin cancer is accomplished by digital image processing. Thresholding, Filtering, Feature extraction, Segmentation, and Recognition are some of the techniques used in this. The system will then detect the diseased or cancerous area. A segmentation algorithm that can effectively detect skin melanoma pixels in the information image is needed. The systems input is a dermoscopic image, which is then processed using novel image processing techniques. A series of Dermoscopic Images is used in pre-processing to detect various stages, and the images are filtered using Dull Razor filtering to eliminate hairs and air bubbles in the image. Thresholding techniques are used to identify the regions area, which is then recognized qualitatively and quantitatively. Keywords: Skin cancer, Segmentation, Thresholding, Melanoma Detection, Digital Image, Carcinoma, feature extraction.