Bowyer, K., Kranenburg, C. and Dougherty, S. (1999) Edge Detector Evaluation Using Empirical ROC Curves Service Productivity and Value Co-Creation View project Social Acceptance of Autonomous Trucks View Project Edge Detector Evaluation Using Empirical ROC Curves.

has been cited by the following article:

• TITLE: Performance Evaluation of Edge Detection Using Sobel, Homogeneity and Prewitt Algorithms

  AUTHORS: Abdel Karim M. Baareh, Ahmad Al-Jarrah, Ahmad M. Smadi, Ghazi H. Shakah

  KEYWORDS: Edge Detector, Edge Enhancement, Edge Localization, Smoothing, Image Processing

  JOURNAL NAME: Journal of Software Engineering and Applications, Vol.11 No.11, November 30, 2018

  ABSTRACT: 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.