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Performance Evaluation of Image Edge Detection Techniques
Maher I. Rajab
Pages - 170 - 185     |    Revised - 31-10-2016     |    Published - 01-12-2016
Published in International Journal of Computer Science and Security (IJCSS)
Volume - 10   Issue - 5    |    Publication Date - December 2016  Table of Contents
MORE INFORMATION
References   |   Abstracting & Indexing
KEYWORDS
Image Edge Detection, Gaussian Noise, Gaussian Smoothing.
ABSTRACT
The success of an image recognition procedure is related to the quality of the edges marked. The aim of this research is to investigate and evaluate edge detection techniques when applied to noisy images at different scales. Sobel, Prewitt, and Canny edge detection algorithms are evaluated using artificially generated images and comparison criteria: edge quality (EQ) and map quality (MQ). The results demonstrated that the use of these criteria can be utilized as an aid for further analysis and arbitration to find the best edge detector for a given image.
ABSTRACTING & INDEXING
1 Google Scholar 
2 refSeek 
3 Scribd 
4 SlideShare 
5 PdfSR 
REFERENCES
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M. Sonka, V. Hlavac, R. Boyle. Image Processing, Analysis, and Machine Vision. Toronto, CA: Thomson, 2008, pp. 132-146.
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W.K. Pratt. Digital Image Processing, New York: Wiley InterSciencce, 1991.
MANUSCRIPT AUTHORS
Associate Professor Maher I. Rajab
College of Computer & Information Systems Computer Engineering Department Umm Al-Qura University Makkah 21955, Saudi Arabia - Saudi Arabia
mirajab@uqu.edu.sa


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