Automated vehicle detection in forward-looking infrared imagery

被引：23

作者：

Der, S ^{[1
]}

Chan, A ^{[1
]}

Nasrabadi, N ^{[1
]}

Kwon, H ^{[1
]}

机构：

[1] USA, Res Lab, Adelphi, MD 20783 USA

来源：

APPLIED OPTICS | 2004年 / 43卷 / 02期

关键词：

D O I：

10.1364/AO.43.000333

中图分类号：

O43 [光学];

学科分类号：

070207 ; 0803 ;

摘要：

We describe an algorithm for the detection and clutter rejection of military vehicles in forward-looking infrared (FLIR) imagery. The detection algorithm is designed to be a prescreener that selects regions for further analysis and uses a spatial anomaly approach that looks for target-sized regions of the image that differ in texture, brightness, edge strength, or other spatial characteristics. The features are linearly combined to form a confidence image that is thresholded to find likely target locations. The clutter rejection portion uses target-specific information extracted from training samples to reduce the false alarms of the detector. The outputs of the clutter rejecter and detector are combined by a higher-level evidence integrator to improve performance over simple concatenation of the detector and clutter rejecter. The algorithm has been applied to a large number of FLIR imagery sets, and some of these results are presented here. (C) 2004 Optical Society of America.

引用

页码：333 / 348

页数：16

共 13 条

[1] AUTOMATIC TARGET RECOGNITION - STATE-OF-THE-ART SURVEY [J].