Automatic Feature Recognition for GPR Image Processing
Commenced in January 2007
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Automatic Feature Recognition for GPR Image Processing

Authors: Yi-an Cui, Lu Wang, Jian-ping Xiao

Abstract:

This paper presents an automatic feature recognition method based on center-surround difference detecting and fuzzy logic that can be applied in ground-penetrating radar (GPR) image processing. Adopted center-surround difference method, the salient local image regions are extracted from the GPR images as features of detected objects. And fuzzy logic strategy is used to match the detected features and features in template database. This way, the problem of objects detecting, which is the key problem in GPR image processing, can be converted into two steps, feature extracting and matching. The contributions of these skills make the system have the ability to deal with changes in scale, antenna and noises. The results of experiments also prove that the system has higher ratio of features sensing in using GPR to image the subsurface structures.

Keywords: feature recognition, GPR image, matching strategy, salient image

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1075342

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References:


[1] Daniels DJ, Ground Penetrating Radar (2nd Edition). Knoval (Institution of Engineering and Technology). pp. 1-4, (2004).
[2] Miao JIN, Yonghui ZHAO, Jiansheng WU and Xiongyao XIE, "Gradient Method to Extract ROI of GPR Image", Journal of Image and Graphics, Vol. 14, No. 4, pp. 579-584, April 2009.
[3] Jin-feng Hu, Zheng-ou Zhou "Target Detection and Orientation in Subsurface Penetrating Radar Data " , Chinese Journal of Scientific Instrument, Vol. 27, No. 4, pp. 372-375, April 2006.
[4] M Heisenberg and R Wolf, Studies of Brain Function, Springer-Verlag Press, Berlin, 1984.
[5] T Eduardo and C Torras, "Detection of Nature Landmarks through Multiscale Opponent Features", Proceedings of International Conference on Pattern Recognition, Barcelona, pp. 976-979, September 2000.
[6] W Sheng and B Xia, "Texture segmentation method based on Gabor ring filtering", Infrared and Laser Engineering (in Chinese), Vol. 32, No. 5, pp. 484-488, 2003.
[7] K Mikolajczyk and C Schmid, "Scale & affine Invariant Interest Point Detectors", International Journal of Computer Vision, Vol. 60, No. 1, pp. 63-86, 2004.
[8] L Wang and Z X Cai, "Saliency based natural landmarks detection under unknown environments", Pattern recognition and artificial intelligence (in Chinese), Vol. 31, No. 1, pp. 46-51, 2006.
[9] D Lowe, "Object Recognition from Local Scale Invariant Features", Proceedings of the International Conference on Computer Vision, Greece, pp. 1150-1157, September 1999.