DocumentCode :
2668342
Title :
Remote sensing with Spotter [land mine detection]
Author :
Jarrad, Geoff A. ; McMichael, Daniel W.
Author_Institution :
Centre for Sensor Signal & Inf. Process., Mawson Lakes, SA, Australia
fYear :
1999
fDate :
1999
Firstpage :
413
Lastpage :
418
Abstract :
Spotter is a flexible extensible software tool for interactive development, application and testing of algorithms for detecting objects in multispectral imagery. Images from different sensors are registered, and low level features are extracted. Feature selection and reduction algorithms generate reduced dimension feature sets. Feature images are soft classified, pixel by pixel, and the output is used to drive a preliminary detection process to identify regions of interest (ROI). Geometric features are extracted from the ROI, which are then soft classified, and a detection decision is made for each. Many algorithms are provided, including Gaussian mixture model classifiers and shared mixture classifiers. Mixture of experts classifiers enable physically inspired classifiers to be incorporated to complement statistical designs
Keywords :
buried object detection; feature extraction; image classification; interactive systems; military systems; remote sensing; Gaussian mixture model classifiers; Spotter; classification; feature images; feature reduction; feature selection; flexible extensible software tool; geometric feature extraction; image registration; interactive development; interactive testing; land mine detection; low-level feature extraction; multispectral imagery; object detection; remote sensing; shared mixture classifiers; Application software; Feature extraction; Landmine detection; Multispectral imaging; Object detection; Pixel; Remote sensing; Software algorithms; Software testing; Software tools;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information, Decision and Control, 1999. IDC 99. Proceedings. 1999
Conference_Location :
Adelaide, SA
Print_ISBN :
0-7803-5256-4
Type :
conf
DOI :
10.1109/IDC.1999.754193
Filename :
754193
Link To Document :
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