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Human beings are highly prone to bone fractures, to a great extent as an outcome of accidents or other factors such as bone cancer. Manual fracture detection takes a lengthy time and comes with a considerable chance of error. As a result, establishing a computer-based method to reduce fracture bone diagnosis time and risk of error is critical. The most common method for segmenting images based on sharp changes in intensity is edge detection. Sobel, Robert, Canny, Prewitt, and LoG (Laplacian of Gaussian) are some of the edge detection approaches that are examined for the study of bone fracture detection. The focal point of this paper is an endeavor to study, analyze and compare the Sobel, Canny, and Prewitt Techniques for detecting edges and identifying the fracture.