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Multispectral image feature selection for land mine detection

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5 Author(s)
G. A. Clark ; Lawrence Livermore Nat. Lab., CA, USA ; S. K. Sengupta ; W. D. Aimonetti ; F. Roeske
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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

Published in:

IEEE Transactions on Geoscience and Remote Sensing  (Volume:38 ,  Issue: 1 )