Landmine Detection from GPR Images With Gauss Gradient Method

Document Type : Original Article

Authors

1 Faculty of Engineering, Zagazig University, Zagazig, Egypt.

2 Faculty of Computer and Information Sciences, Princess Nourah University, Riyadh, Saudi Arabia.

3 Dept. of Electronics and Electrical Communications, Faculty of Electronic Engineering, Menoufia University, Menouf, Egypt.

Abstract

Ground-Penetrating Radar (GPR) represents an efficient technique for landmine detection. Image processing methods are applied on GPR images in order to reduce the false alarms generated due to the environmental distortions and clutter. This paper presents an efficient method for landmine detection from GPR images depending on the gauss gradient method. The main idea is to apply the Gauss gradient on landmine images as a differentiator to reinforce the landmine objects in the image if existing. After that, both the image histogram and cumulative histogram are estimated. From the obtained histograms for images with and without landmines, we can set a threshold value on the cumulative histogram curve to differentiate between the cases of existing and absent landmine. Simulation results show the success of the proposed method in detecting landmines from GPR images.

References

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Techniques Using Multiple Sensors: A Review”, Subsurface Sensing Technologies
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a report to the U.S.EPA, Nov. 25, 2000.
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data”, caa conference ,1994, pp.175-179.
11. R.grimberg,R.stelgmann,N.iftimie and A.savin , “Ground Penetrating Radar as tool
for nondestructive evaluation of soil”, 6th NDT6th European Conference on Non
Destructive Testing, Oct 2011 , pp.10-12 .
12. D. Hunter, “ Ground penetrating Radar: A review of the basics”, poster, November
2010, pp1-3.
13. A. K. Hocaoglu, P. D. Gader, J. M. Keller and B. N. Nelson , “Anti-Personnel Land
Mine Detection and Discrimination using Acoustic Data”, International Journal of
Subsurface Sensing Technologies and Applications, April 2002 .
14. U. S. khan, w. Al nuaimy and F. E. AbdEL.Samie, “Detection of landmines and
underground utilities from acoustic and GPR images with cepstral approach”,
journal of Visual Communication and Image Representation., May 2010 , pp. 730-
740.
15. R. SakagushiL. M. Collins, L. W. Nolte and G. Sapiro, “Image processing methods
applied to landmine detection in GPR”, Proquest LLC 2013, pp. 17-36.
16. S.Sekhar, F.E.Abd El-Samie, Panyu, W.Al-Nuaimy,and A.K.Nadi, “Automated
Localization Of Retinal Features”, Applied Optics, July 2011.
17. P. A. Torrione, K. D. Morton, R. Sakaguchi, and L. M. Collins “Histograms of
Oriented Gradients for Landmine Detection in Ground-Penetrating Radar Data”,
IEEE Transactions On Geoscience And Remote Sensening , vol. 52, no. 3, March
2014.
18. N. Dalal and B. Triggs, “Histograms of oriented gradients for humandetection,” in
Proc. IEEE Comput. Soc. Conf. Comput. Vis. PatternRecognit., vol. 1. Jun. 2005,
pp. 886–893.

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