文章基本信息

标题：Performance Evaluation of Edge Detection Using Sobel, Homogeneity and Prewitt Algorithms
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作者：Abdel Karim M. Baareh ; Ahmad Al-Jarrah ; Ahmad M. Smadi 等
期刊名称：Journal of Software Engineering and Applications
印刷版ISSN：1945-3116
电子版ISSN：1945-3124
出版年度：2018
卷号：11
期号：11
页码：537-551
DOI：10.4236/jsea.2018.1111032
语种：English
出版社：Scientific Research Publishing
摘要：Edge detection considered as very important and fundamental tool in image processing. An image edge is a very sensitive place where the image information and details mostly placed on it. Different filters were used to detect and enhance these edges to improve the sharpness and raising the image clarity. The significance of this paper comes from the study, compare and evaluate the effects of three well-known edge detection techniques in a spatial domain, where this evaluation was performed using both subjective and objective manner to find out the best edge detection algorithm. The Sobel, Homogeneity and Prewitt algorithms were used on 2D gray-scale synthesis and real images in Jordan using C# programming language. According to the comparative results obtained using the three techniques, it was clearly found that Prewitt and Homogeneity algorithms performance were better than Sobel algorithm. Therefore, Prewitt and Homogeneity algorithms can be recommended as useful detection tools in edge detection.
关键词：Edge Detector;Edge Enhancement;Edge Localization;Smoothing;Image Processing