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A comparative study of edge detection techniques on different images using Scilab
(G.B. Pant University of Agriculture and Technology, Pantnagar - 263145 (Uttarakhand), 2021-01) Rajshree Kumari; Ashok Kumar
In the field of image processing, edge detection plays a significant role in recent years to detect images more accurately, for this purpose it is important to choose the edge detection techniques wisely and correctly based on their properties. Therefore this work aims to give a comparative study of different edge detection technique using some parameters to check which techniques gives more accurate result with some parameters. The aim of this research is to study different edge detection to detect edges under different circumstances. In this research we have proposed a comparative study between the three-edge detection techniques Canny, Sobel, and Prewitt, using different types of images under different parameters for analysis. The software tool that we have used here is Scilab which is an open source tool and an alternative to MATLAB. This study is tested by conducting experiments on the WANG image dataset and benchmark standard images. The results of this comparative studyz suggest that Prewitt works better than other edge detections with greater accuracy under certain parameters and in different image types.