Multispectral image feature selection for land mine detection

The authors' system uses a camera that acquires registered images in six spectral bands and a supervised-learning algorithm to detect metal and plastic land mines. Results show that even with a small sample size, the detection performance is good and holds promise for future work with larger da...

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Bibliographic Details
Published in:	IEEE transactions on geoscience and remote sensing Vol. 38; no. 1; pp. 304 - 311
Main Authors:	Clark, G.A., Sengupta, S.K., Aimonetti, W.D., Roeske, F., Donetti, J.G.
Format:	Journal Article
Language:	English
Published:	New York, NY IEEE 01-01-2000 Institute of Electrical and Electronics Engineers The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Algorithms Applied geophysics ARMS CONTROL Cameras Cascading style sheets Earth sciences Earth, ocean, space Exact sciences and technology EXPLOSIVES Helicopters IMAGE PROCESSING Internal geophysics Land mines Landmine detection Layout MILITARY EQUIPMENT MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEFENSE Multispectral imaging MULTISPECTRAL SCANNERS PATTERN RECOGNITION Pixel Plastics Remote sensing Sea measurements Spectral bands Target recognition VERIFICATION VISIBLE SPECTRA algorithms detection filtering imagery
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Summary:	The authors' system uses a camera that acquires registered images in six spectral bands and a supervised-learning algorithm to detect metal and plastic land mines. Results show that even with a small sample size, the detection performance is good and holds promise for future work with larger data sets.
Bibliography:	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 ObjectType-Article-2 ObjectType-Feature-1 USDOE W-7405-ENG-48
ISSN:	0196-2892 1558-0644
DOI:	10.1109/36.823923