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New Edge Detection Enhancement Method based on Cooperation between Edge Algorithms

by Ashraf A. Nijim, Muhammad T. Abo Kresha, Reda Abo Alez
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 91 - Number 7
Year of Publication: 2014
Authors: Ashraf A. Nijim, Muhammad T. Abo Kresha, Reda Abo Alez
10.5120/15896-5135

Ashraf A. Nijim, Muhammad T. Abo Kresha, Reda Abo Alez . New Edge Detection Enhancement Method based on Cooperation between Edge Algorithms. International Journal of Computer Applications. 91, 7 ( April 2014), 41-47. DOI=10.5120/15896-5135

@article{ 10.5120/15896-5135,
author = { Ashraf A. Nijim, Muhammad T. Abo Kresha, Reda Abo Alez },
title = { New Edge Detection Enhancement Method based on Cooperation between Edge Algorithms },
journal = { International Journal of Computer Applications },
issue_date = { April 2014 },
volume = { 91 },
number = { 7 },
month = { April },
year = { 2014 },
issn = { 0975-8887 },
pages = { 41-47 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume91/number7/15896-5135/ },
doi = { 10.5120/15896-5135 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:12:10.915111+05:30
%A Ashraf A. Nijim
%A Muhammad T. Abo Kresha
%A Reda Abo Alez
%T New Edge Detection Enhancement Method based on Cooperation between Edge Algorithms
%J International Journal of Computer Applications
%@ 0975-8887
%V 91
%N 7
%P 41-47
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Edge detection algorithms are important tools in image processing applications for carrying out much information and being relatively easy to produce. Sobel; Canny; and logarithmic algorithms [1] are among several edge detection algorithms used frequently nowadays. The evalution of such edge detection algorithms is an old problem. Authors [1][3] tend to use visual evaluation that limits the comparison between different edge images. In this paper, we present a new edge enhancement method and five different measures that can be used to statistically evaluate edge detection algorithms. The new edge enhancement method is based on cooperation between different edge detection algorithms. The new edge preserves the advantages of each edge image. Experimental results using two edge detection algorithms proved the efficiency of this method.

References
  1. Ritter, G. X. , and Wilson J. N. 2001. Handbook of Computer Vision Algorithms in Image Algebra. Second Edition. CRC Press.
  2. Ali, M. , and Clausi, D. 2001. Using The Canny Edge Detector for Feature Extraction and Enhancement of Remote Sensing Images. IEEE Geoscience and Remote Sensing Symposium. 2298-2300.
  3. Shrivakshan, G. T. , and Chandrasekar, C. , 2012. A Comparison of various Edge Detection Techniques used in Image Processing. IJCSI International Journal of Computer Science Issues, Vol. 9, Issue 5, No 1. 269-276.
  4. Tan, H. L. , Li, Z. , Tan, Y. H. , Rahardja, S. , and Yeo C. 2013. A perceptually Relevant MSE-Based Image Quality Metric. IEEE Transactions on Image Processing, Vol. 22, No. 11. 4447-4459.
  5. Huynh-Thu, Q. , and Ghanbari, M. 2008. Scope of validity of PSNR in image/video quality assessment. Electronic Letters, Vol. 44, Issue 13. 800-801.
  6. Staal, J. J. , Abramoff, M. D. , Niemeijer, M. , Viergever, M. A. , and van Ginneken, B. 2004. Ridge based vessel segmentation in color images of the retina. IEEE Transactions on Medical Imaging, vol. 23. 501-509.
  7. Niemeijer, M. , Staal, J. J. , van Ginneken, B. , Loog, M. , and Abramoff, M. D. 2004. Comparative study of retinal vessel segmentation methods on a new publicly available database. SPIE Medical Imaging, Vol. 5370. 648-656.
  8. Shannon, C. E. 1948. A Mathematical Theory of Communication. Bell System Technical Journal, 27 (3). 379–423.
  9. Shannon, C. E. , and Weaver, W. 1949. The Mathematical Theory of Communication. University of Illinois Press.
  10. Hu, M. K. 1961. Pattern recognition by moment invariants, Proc. IRE49. 1428.
  11. Hu, M. K. 1962. Visual problem recognition by moment invariant. IRE Trans. Inform. Theory. Vol. IT-8. 179-187.
  12. Rizon, M. , Yazid, H. , Saad, P. , Shakaff, A. Y. , Saad, A. , Mamat, M. R. , Yaacob, S. , Desa, H. , and Karthigayan, M. 2006. Object Detection using Geometric Invariant Moment. American Journal of Applied Science 2 (6). 1876-1878.
  13. El-Sayed, M. 2011. A New Algorithm Based Entropy Threshold for Edge Detection in Images. IJCSI International Journal of Computer Science Issues. Vol. 8, Issue 5, No 1. 71-78.
  14. Vidya, P. , Veni, S. , and Narayanankutty K. A. 2009. Performance Analysis of Edge Detection Methods on Hexagonal Sampling Grid. International Journal of Electronic Engineering Research. Vol. 1, No. 4. 313-328.
  15. Signal and Image Processing Institute. The USC Texture Mosaic Images. USC University of Southern California. http:// sipi. usc. edu.
  16. Laws, K. I. 1980. Textured Image Segmentation. PhD thesis, University of Southern California. USCIPI. Report 940.
  17. Neto, A. M. , Rittner, L. , Leite, N. , Zampieri, D. E. , Lotufo, R. , and Mendeleck, A. 2007. Pearson's Correlation Coefficient for Discarding Redundant Information in Real Time Autonomous Navigation System. IEEE Multi-conference on Systems and Control, Cingapura.
  18. Neto, A. M. , Victorino, A. C. , Fantoni, I. , and Zampieri, D. E. 2011, Automatic Regions-of-Interest Selection based on Pearson's Correlation Coefficient. IROS Workshop on Visual Control of Mobile Robots (ViCoMoR), San Francisco, USA.
Index Terms

Computer Science
Information Sciences

Keywords

Edge detection Canny edge detector Sobel edge detector logarithmic edge detector MSE PSNR PCC Shannon Entropy Hu-moments.

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