The purpse of this final thesis was to analyze and compare various edge detection algorithms and to implement them. Prewitt, Sobel, Robert’s cross, Canny, Laplacian and Laplacian of Gaussian edge detectors were defined and analyzed in this thesis. First three are based on gradient method and they are first derivative edge detectors, last two are based on Laplacian method and they are second derivative edge detectors. Prewitt and Sobel are used for edge detection in vertical and horizontal direction and Robert’s cross is used for detecting an edge with angle of 45 degrees. If with averaging gradient magnitude we want to keep the details too, we need to use Sobel detector instead of Prewitt. If we are processing a picture with a lot of noise, Prewitt will be a little bit better then Sobel detector and a lot better than Robert’s cross detector. For Canny we can say that it is improved version of some of these three edge detectors, even Sobel is most used as a basis for Canny detector. On that basis algorithm Canny adds a few more operations which add more precision for detecting an edge and also provides edge thinning. Laplacian and Gaussian of Laplacian have only one convolution matrix (and other edge detecion algorithms have two) and that is the reason they are faster than the others.