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Edge Detection in blurred images using Ant Colony Optimization Techniques
S. Agarwal1
Section:Research Paper, Product Type: Isroset-Journal
Vol.1 ,
Issue.2 , pp.21-24, Mar-2013
Online published on Apr 30, 2013
Copyright © S. Agarwal . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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IEEE Style Citation: S. Agarwal, “Edge Detection in blurred images using Ant Colony Optimization Techniques,” International Journal of Scientific Research in Computer Science and Engineering, Vol.1, Issue.2, pp.21-24, 2013.
MLA Style Citation: S. Agarwal "Edge Detection in blurred images using Ant Colony Optimization Techniques." International Journal of Scientific Research in Computer Science and Engineering 1.2 (2013): 21-24.
APA Style Citation: S. Agarwal, (2013). Edge Detection in blurred images using Ant Colony Optimization Techniques. International Journal of Scientific Research in Computer Science and Engineering, 1(2), 21-24.
BibTex Style Citation:
@article{Agarwal_2013,
author = {S. Agarwal},
title = {Edge Detection in blurred images using Ant Colony Optimization Techniques},
journal = {International Journal of Scientific Research in Computer Science and Engineering},
issue_date = {3 2013},
volume = {1},
Issue = {2},
month = {3},
year = {2013},
issn = {2347-2693},
pages = {21-24},
url = {https://www.isroset.org/journal/IJSRCSE/full_paper_view.php?paper_id=34},
publisher = {IJCSE, Indore, INDIA},
}
RIS Style Citation:
TY - JOUR
UR - https://www.isroset.org/journal/IJSRCSE/full_paper_view.php?paper_id=34
TI - Edge Detection in blurred images using Ant Colony Optimization Techniques
T2 - International Journal of Scientific Research in Computer Science and Engineering
AU - S. Agarwal
PY - 2013
DA - 2013/04/30
PB - IJCSE, Indore, INDIA
SP - 21-24
IS - 2
VL - 1
SN - 2347-2693
ER -
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Abstract :
This paper defines edge detection and prioritization in blurred images. Edge Detection has been center of concern in image processing, as this help to distinguish object from the system and draw boundaries. A large number of powerful and effective techniques exist for edge detection in digital images. But sometimes our image is not clear, it is blurred. All edge detection algorithms are not able to process such blurred images. So by using ant colony optimization technique it is possible to detect and prioritize edges in blurred images.
Key-Words / Index Term :
ACO Ant Colony Optimization, ED Edge Detection, IP Image Processingt,SM-Ant bot system,SAant bot system
References :
[1]. M. Dorigo and S. Thomas, Ant Colony Optimization. Cambridge: MIT Press, 2004.
[2]. Jing Tian, Weiyu Yu, and Shengli Xie, “An Ant Colony Optimization Algorithm For Image Edge Detection”, in Proc. of the IEEE International, pp.751-756,2008.
[3]. Hossein Nezamabadi-pour • Saeid Saryazdi Esmat Rashedi, “Edge detection using ant algorithms”, in proc. of Springer-Verlag, pp.623-628,2005.
[4]. Aleksandar Jevti´c, Joel Quintanilla-Dominguez, M.G. Cortina-Januchs and Diego Andina, “Edge Detection Using Ant Colony Search Algorithm and Multiscale Contrast Enhancement”, in the Proceedings of the 2009 IEEE International Conference on systems, man, and cybernetics, pp.2193-2198,2009.
[5]. X. Zhuang, “Edge Feature Extraction in Digital Images with the Ant Colony System”, in proc. of the IEEE international Conference an computational intelligence for Measurement Systems and Applications, pp. 133-136,2004.
[6]. Alirezae Rezaee, “Extracting edge of images with ant colony”, in the Journal of Electrical Engineering,pp. 57–59,2008.
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