International Journal of Image, Graphics and Signal Processing (IJIGSP)
IJIGSP Vol. 9, No. 4, 8 Apr. 2017
Cover page and Table of Contents: PDF (size: 799KB)
Optimum Fuzzy based Image Edge Detection Algorithm
Full Text (PDF, 799KB), PP.44-55
Views: 0 Downloads: 0
Author(s)
Ajenaghughrure Ighoyota Ben.
1,*
Ogini Nicholas.O.
2
Onyekweli Charles O.
2
Index Terms
Edge detection, algorithm, fuzzy, algorithms, Canny, Prewittt, Sobel, LOG
Abstract
Edge detection is important in image processing to aid operations such as object classification and identification amongst others. This is soley to improve interpretability of the image. Common edge detection techniques such as Sobel, Prewittt, Canny, Laplacian of Gaussian (LOG), Robertss and Zero-Crossing has attracted the attention of researchers to perform a comparative analysis on these techniques excepts fuzzy, using different type of images. Fuzzy logic based edge detection algorithms development and comparison with existing algorithm became important due to the fact that the pixels’ boundaries identifying image degs are crystal clear as expected, hence other edge detection algorithms using crisp values will be omitting some vital information pixels, this impairs the quality of the image edge detected and further application through proper interpretation. This research further extends the investigation of edge detection techniques optimality, through comparing Sobel, Prewittt, Canny, Laplacian of Gaussian (LOG), and Robertss edge detection algorithms with our proposed fuzzy based edge detection algorithm designed using MATLAB. The result indicated that the novel fuzzy based edge detection algorithm developed in this research outperforms the Canny, Sobel, Prewittt, Robertss and LOG edge detection algorithms in three different experiments with different images
Cite This Paper
Ajenaghughrure Ighoyota Ben, Ogini Nicholas.O., Onyekweli Charles O.,"Optimum Fuzzy based Image Edge Detection Algorithm", International Journal of Image, Graphics and Signal Processing(IJIGSP), Vol.9, No.4, pp.44-55, 2017. DOI: 10.5815/ijigsp.2017.04.06
Reference
[1]Felix Bachofer, Geraldine Quénéhervé, Thimm Zwiener,Michael Maerker and Volker Hochschild, Comparative analysis of Edge Detection techniques for SAR images European Journal of Remote Sensing - Vol49: pp 205-224, 2016.
[2]Raman Maini & Himanshu Aggarwal, Study and Comparison of Various Image Edge Detection Techniques International Journal of Image Processing (IJIP), Volume (3) : Issue (1), pp1-12, February 2009.
[3]S.K. Katiyar P.V. Arun, Comparative analysis of common edge detection techniques in context of object extraction, IEEE Transactions on Geosciences and Remote Sensing, Vol. 50, NO. 11b, pp 68-79, November 2012
[4]Zakir Hussain1, Diwakar Agarwal, A comparative analysis of edge detection techniques used in flame image processing, International Journal of Advance Research In Science And Engineering IJARSE, Vol. No.4, Special Issue (01), pp1335-1343, March 2015
[5]Parvinder Singh Sandhu, Mamta Juneja and Ekta Walia,Comparative Analysis of Edge Detection Techniques for extracting Refined Boundaries 2009 International Conference on Machine Learning and Computing IPCSIT vol.3 (2011) © (2011) IACSIT Press, Singapore PP1-10
[6]T. Dharani I. Laurence Aroquiaraj V. Mageshwari, Comparative Analysis of Edge Detection Algorithms Based on Content Based Image Retrieval With Heterogeneous Images, International Journal of Computational Intelligence and Informatics, Vol. 5: No. 4, pp374-38, March 2016
[7]Shaveta Malik, Tapas Kumar, Comparative Analysis of Edge Detection between Gray Scale and Color Image Communications on Applied Electronics (CAE) – ISSN : 2394-4714 Foundation of Computer Science FCS, New York, USA Volume 5– No. 2, 38 -43, May 2016
[8]Vineet Saini, Rajnish Garg, A Comparative Analysis on Edge Detection Techniques Used in Image Processing, IOSR Journal of Electronics and Communication Engineering (IOSRJECE) ,Volume 1, Issue 2, PP 56-59, May-June 2012,
[9]Canny, John, "A Computational Approach to Edge Detection," IEEE Transactions on Pattern Analysis and Machine I ntelligence,Vol. PAMI-8, No. 6, pp. 679-698. 1986
[10]Lim, Jae S., Two-Dimensional Signal and Image Processing, Englewood Cliffs, NJ, Prentice Hall, pp. 478-488, 1990
[11]Parker, James R., Algorithms for Image Processing and Computer Vision, New York, John Wiley & Sons, Inc., pp. 23-29. 1997.Abdel-Qader, I., Abudayyeh, O., and Kelly, M. "Analysis of Edge-Detection Techniques for Crack Identification in Bridges." journal of computing in civil engineering, Volume 17, Issue 4, pp255-263, October 2003.