Abstract
This article studies a comprehensive methods of edge detection and algorithms in digital images which is reflected a basic process in the field of image processing and analysis. The purpose of edge detection technique is discovering the borders that distinct diverse areas of an image, which donates to refining the understanding of the image contents and extracting structural information. The article starts by clarifying the idea of an edge and its importance in image analysis and studying the most noticeable edge detection methods utilized in this field, (e.g. Sobel, Prewitt, and Canny filters), besides other schemes based on distinguishing unexpected modifications in light intensity and color gradation. The research as well discusses the benefits and limitations of each technique, emphasizing their efficacy in addressing various kinds of images and the dares they face in complex environs. This article offers a comparative analysis of the numerous approaches utilized in edge detection, which assistances in selecting the suitable technique according to the requirements of applications, like video processing, object recognition, medical image analysis, and computer vision.

Key words: Edge detection, Gradient, Gaussian