Multispectral image feature selection for land mine detection

Author

Clark, Gregory A. ; Sengupta, Sailes K. ; Aimonetti, William D. ; Roeske, Frank ; Donetti, John G.

Author_Institution

Lawrence Livermore Nat. Lab., CA, USA

Volume

38

Issue

1

fYear

2000

fDate

1/1/2000 12:00:00 AM

Firstpage

304

Lastpage

311

Abstract

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

Keywords

buried object detection; feature extraction; geophysical signal processing; geophysical techniques; image processing; military systems; multidimensional signal processing; remote sensing; terrain mapping; IR method; buried object detection; camera; detection performance; feature extraction; geophysical measurement technique; image feature selection; image processing; infrared imaging; land mine detection; land surface; landmine; metal; military system; multispectral remote sensing; optical imaging; plastic land mine; registered image; supervised-learning algorithm; terrain mapping; visible region; Cameras; Cascading style sheets; Helicopters; Landmine detection; Layout; Multispectral imaging; Pixel; Plastics; Sea measurements; Target recognition;

fLanguage

English

Journal_Title

Geoscience and Remote Sensing, IEEE Transactions on

Publisher

ieee

ISSN

0196-2892

Type

jour

DOI

10.1109/36.823923

Filename

823923