An Analysis of Edge Detection Methodologies in Spatial and Morphological Perspective

Now-a-days, edge detection through image processing is become core research due to its wide application in different fields such as medical and industries. In digital image processing, edge detection and feature extraction are considered as an active research area. Different researcher has designed different methods (i.e.- Prewitt, Sobel, and Roberts) for edge detection in images for better visualization result. The basic purpose of edge detection process is to interpret pixels values to find more significant, useful, and meaningful information of image. The most important and strong feature in any image is called its edge, which can be detect by using different image processing algorithm. Therefore, fast, simple, and robust method for edge detection is become a basic need for edge detection and feature extraction. In this paper, we propose a morphological based edge detection algorithm, which based on three basic steps (i) Image Acquisition, (ii) Image enhancement and (iii) Morphological edge detection filter. In the result, we compare proposed algorithm with existing spatial domain algorithm i.e.- Prewitt, Sobel, Laplacian of Gaussian, and kirsch to show the robustness and efficiency of proposed morphological algorithm. Moreover, we did a quality-based comparison of all edge detection algorithm by using different quality matrix. After doing the comparison, it is clear that the performance of proposed algorithm is better than the existing in term of time, efficiency and quality.