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Proceedings Paper

Recognition of tanks using laser radar (LADAR) images
Author(s): Haim Garten; Yoram Tal; Yoram Swirski; Amir Imber
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Paper Abstract

Three-dimensional sensors based on Laser Radar (LADAR) technology possess vast potential for the future battlefield. This work presents an algorithm for the recognition of T62 and T72 tanks from 3D imagery. The algorithm consists of several stages: a) Pre-processing of LADAR images to remove range noise and to determine ground level. b) Segmentation to extract regions that fulfill certain pre-defined conditions. c) Extraction of specific tank features from each region. d) Applying a Fuzzy Logic classifier on the feature vector to discriminate between T62 or T72 tanks and other type of targets or natural clutter. A commercial airborne LADAR sensor was used to acquire images from an area of 40 square kilometers with a measurement density of 20 pixels per square meter and a range noise of 15 cm (1 sigma). The images included more than a hundred man-made objects (tanks, armored personnel carriers, trucks, cranes)along with natural clutter (vegetation and boulders). Among the targets were 18 tanks, two of which were covered with a camouflage net. The algorithm recognized the 16 uncovered tanks with a False Alarm Rate (FAR) of 0.025 per square kilometer. This FAR value is better than the respective FAR values derived for 2D Imaging where Automatic Target Recognition (ATR) techniques are applied. These results show promise for automatic recognition of various targets employing LADAR sensors.

Paper Details

Date Published: 8 December 2004
PDF: 11 pages
Proc. SPIE 5613, Military Remote Sensing, (8 December 2004); doi: 10.1117/12.577831
Show Author Affiliations
Haim Garten, RAFAEL Armament Development Authority Ltd. (Israel)
Yoram Tal, RAFAEL Armament Development Authority Ltd. (Israel)
Yoram Swirski, RAFAEL Armament Development Authority Ltd. (Israel)
Amir Imber, RAFAEL Armament Development Authority Ltd. (Israel)

Published in SPIE Proceedings Vol. 5613:
Military Remote Sensing
Gary W. Kamerman; David V. Willetts, Editor(s)

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