Feature-based target classification in laser radar

Mark R. Stevens; Magnus Snorrason; Harald Ruda; Sengvieng A. Amphay

doi:10.1117/12.477046

25 July 2002 Feature-based target classification in laser radar

Mark R. Stevens, Magnus Snorrason, Harald Ruda, Sengvieng A. Amphay

Proceedings Volume 4726, Automatic Target Recognition XII; (2002) https://doi.org/10.1117/12.477046
Event: AeroSense 2002, 2002, Orlando, FL, United States

Abstract

Numerous feature detectors have been defined for detecting military vehicles in natural scenes. These features can be computed for a given image chip containing a known target and used to train a classifier. This classifier can then be used to assign a label to an un-labeled image chip. The performance of the classifier is dependent on the quality of the set of features used. In this paper, we first describe a set of features commonly used by the Automatic Target Recognition (ATR) community. We then analyze feature performance on a vehicle identification task in laser radar (LADAR) imagery. Our features are computed over both the range and reflectance channels. In addition, we perform feature subset selection using two different methods and compare the results. The goal of this analysis is to determine which subset of features to choose in order to optimize performance in LADAR Autonomous Target Acquisition (ATA).

Citation Download Citation

Mark R. Stevens, Magnus Snorrason, Harald Ruda, and Sengvieng A. Amphay "Feature-based target classification in laser radar", Proc. SPIE 4726, Automatic Target Recognition XII, (25 July 2002); https://doi.org/10.1117/12.477046

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