In this thesis, we explore the application of edge detection and border detection algorithms in MATLAB for the purpose of skin lesion detection, focusing on melanoma. Specifically, we utilize the Canny and Sobel algorithms to identify and delineate the edges and borders of lesions in dermoscopic images. To assess the similarity of images and effectively detect lesions, we employ Normalized Cross-Correlation (NCC) and Mean Squared Error (MSE) methods. These techniques allow for the comparison of suspected melanoma regions against known samples, facilitating accurate diagnosis. Additionally, we investigate the use of the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm for object detection within the images.