Research Article
Edge Detection for Objects in the Upper Triangle Gray Scale Image by Cholesky Decomposition and Unsharp Masking (USM)
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
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| Volume 85 - Issue 6 |
| Published: January 2014 |
| Authors: Hind Rostom Mohamed Shaban, Ameer Mohammad Husain |
10.5120/14842-3020
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Hind Rostom Mohamed Shaban, Ameer Mohammad Husain . Edge Detection for Objects in the Upper Triangle Gray Scale Image by Cholesky Decomposition and Unsharp Masking (USM). International Journal of Computer Applications. 85, 6 (January 2014), 1-5. DOI=10.5120/14842-3020
@article{ 10.5120/14842-3020,
author = { Hind Rostom Mohamed Shaban,Ameer Mohammad Husain },
title = { Edge Detection for Objects in the Upper Triangle Gray Scale Image by Cholesky Decomposition and Unsharp Masking (USM) },
journal = { International Journal of Computer Applications },
year = { 2014 },
volume = { 85 },
number = { 6 },
pages = { 1-5 },
doi = { 10.5120/14842-3020 },
publisher = { Foundation of Computer Science (FCS), NY, USA }
}
%0 Journal Article
%D 2014
%A Hind Rostom Mohamed Shaban
%A Ameer Mohammad Husain
%T Edge Detection for Objects in the Upper Triangle Gray Scale Image by Cholesky Decomposition and Unsharp Masking (USM)%T
%J International Journal of Computer Applications
%V 85
%N 6
%P 1-5
%R 10.5120/14842-3020
%I Foundation of Computer Science (FCS), NY, USA
Abstract
In this paper , we propose an efficient and effective method for Edge detection for objects in the upper triangle Gray Scale Image . The optimal Edge detection discriminative features of gray scale images are obtained by performing Cholesky decomposition , which could be implemented using the edge existing algorithm. We approach also yields the size of the symmetry region without additional computational effort . Experiments showed that the proposed algorithm could generate a path one pixel wide with continuous edges, and the proposed algorithm had a better edge-detection accuracy than others techniques. Therefore, the proposed edge-detection algorithm is feasible for use in automatic visual inspection systems .
References
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- Nils T Siebel, Sven Grunewald, Gerald Sommer " Creating Edge Detectors by Evolutionary Reinforcement Learning " IEEE Congress on Evolutionary Computation (IEEE World Congress on Computational Intelligence) Year: 2008 Pages: 3553-3560
- http://en. wikipedia. org/wiki/Unsharp_masking
- http://users. cecs. anu. edu. au/~trumpf/UH60Festschrift. pdf.
- http://www. cambridgeincolour. com/tutorials/unsharp-mask . htm
- http://www. astronomy. ohio-state. edu/~pogge/Ast350/Unsharp/
- http://www. scantips. com/simple6. html " A few scanning tips, Sharpening - Unsharp Mask"
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