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Comparative Study of Edge Detection Algorithms Applying on the Grayscale Noisy Image Using Morphological Filter

In this paper, classified and comparative study of edge detection algorithms are presented. Experimental results prove that Boie-Cox, ShenCastan and Canny operators are better than Laplacian of Gaussian (LOG), while LOG is better than Prewitt and Sobel in case of noisy image. Subjective and objective methods are used to evaluate the different edge operators. The morphological filter is more important as an initial process in the edge detection for noisy image and used opening-closing operation as preprocessing to filter noise. Also, smooth the image by first closing and then dilation to enhance the image before the edge operators affect.