Robust Automatic Target Recognition Using Extra-trees

Pisane, Jonathan; Marée, Raphaël; Wehenkel, Louis; Verly, Jacques

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Robust Automatic Target Recognition Using Extra-trees

Pisane, Jonathan; Marée, Raphaël; Wehenkel, Louis et al.

2010 • In Pisane, Jonathan (Ed.) Robust Automatic Target Recognition Using Extra-trees

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https://hdl.handle.net/2268/103113

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Keywords :

Extra-trees; MSTAR; ATR

Abstract :

[en] In this paper, we describe a new automatic target recognition algorithm for classifying SAR images based on the PiXiT image classifier. It uses randomized sub-windows extraction and extremely randomized trees (extra-trees). This approach requires very little pre-processing of the images, thereby limiting the computational load. It was successfully tested on an extended version of the public standard MSTAR database, that includes targets of interest, false targets, and background clutter. A misclassification rate of about three percent has been achieved.

Research center :

INTELSIG - EECS

Disciplines :

Electrical & electronics engineering

Author, co-author :

Pisane, Jonathan ; Université de Liège - ULiège > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Exploitation des signaux et images

Marée, Raphaël ; Université de Liège - ULiège > GIGA-Management : Plateforme bioinformatique

Wehenkel, Louis ; Université de Liège - ULiège > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Systèmes et modélisation

Verly, Jacques ; Université de Liège - ULiège > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Exploitation des signaux et images

Language :

English

Title :

Robust Automatic Target Recognition Using Extra-trees

Publication date :

2010

Event name :

International Radar Conference

Event organizer :

IEEE

Event place :

Washington D.C., United States

Event date :

from 10-05-2010 to 14-05-2010

Audience :

International

Main work title :

Robust Automatic Target Recognition Using Extra-trees

Editor :

Pisane, Jonathan ; Université de Liège - ULiège > Département d'électricité, électronique et informatique (Institut Montefiore) > Exploitation des signaux et images

Publisher :

IEEE

Peer reviewed :

Peer reviewed

Funders :

FRIA - Fonds pour la Formation à la Recherche dans l'Industrie et dans l'Agriculture [BE]

Available on ORBi :

since 15 November 2011

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Bibliography

M. Richards, Fundamentals of radar signal processing. McGraw-Hill, 2005.
A. Rihaczek, "Principles of high-resolution radar," Norwood, MA: Artech House, 1996.
D. Wehner, "High resolution radar," Norwood, MA, Artech House, Inc., 1987, 484 p., 1987.
F. Sadjadi, Physics of Automatic Target Recognition. Springer; 1st edition, Feb. 2007.
B. Javidi, Image Recognition and Classification: Algorithms, Systems, and Applications. CRC Press, 2002.
J. Pisane, R. Marée, P. Ries, L. Wehenkel, and J. Verly, "An extra-trees-based automatic target recognition algorithm," in Proc. International Radar Conference, Oct 2009.
R. Marée, P. Geurts, J. Piater, and L. Wehenkel, "Random subwindows for robust image classification," in Proc. IEEE CVPR, vol. 1, 2005, pp. 34-40.
M. Cetin, W. Karl, and D. Castanon, "Analysis of the impact of feature-enhanced SAR imaging on ATR performance," in Proceedings of SPIE, vol. 4727, 2002, pp. 134-145.
N. Hernandez, J. Rodriguez, J. Martin, F. Mata, R. Gonzalez, and R. Alvarez, "An Approach to Automatic Target Recognition in Radar Images Using SVM," Lecture Notes in Computer Science, vol. 4225, p. 964, 2006.
S. Park, M. Smith, and R. Mersereau, "Target Recognition Based on Directional Filter Banks and Higher-Order Neural Networks," Digital Signal Processing, vol. 10, no. 4, pp. 297-308, 2000.
R. Patnaik and D. Casasent, "MINACE filter classification algorithms for ATR using MSTAR data," in Proc. SPIE, vol. 5807, 2005, pp. 100-111.
Y. Sun, Z. Liu, S. Todorovic, and J. Li, "Synthetic aperture radar automatic target recognition using adaptive boosting," in Proc. SPIE, vol. 5808, 2005, pp. 282-293.
Y. Yang, Y. Qiu, and C. Lu, "Automatic Target Classification: Experiments on the MSTAR SAR Images," in Sixth International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, 2005 and First ACIS International Workshop on Self-Assembling Wireless Networks. SNPD/SAWN 2005, 2005, pp. 2-7.
Q. Zhao and J. Principe, "Support vector machines for SAR automatic target recognition," IEEE Transactions on Aerospace and Electronic Systems, vol. 37, no. 2, pp. 643-654, 2001.
Q. Zhao, D. Xu, and J. Principe, "Pose estimation of SAR automatic target recognition," in Proceedings of Image Understanding Workshop, Monterey, CA, vol. 11, 1998.
R. Marée, P. Geurts, and L. Wehenkel, "Random subwindows and extremely randomized trees for image classification in cell biology," BMC Cell Biology supplement on Workshop of Multiscale Biological Imaging, Data Mining and Informatics, vol. 8, no. S1, July 2007.
R. Marée, "PiXiT, an automatic image classification software in Java."
P. Geurts, D. Ernst, and L. Wehenkel, "Extremely randomized trees," Machine Learning, vol. 36, no. 1, pp. 3-42, 2006.
L. Breiman, J. Friedman, R. Olsen, and C. Stone, Classification and Regression Trees. Wadsworth International (California), 1984.
L. Wehenkel, Automatic Learning Techniques in Power Systems. Kluwer Academic Publishers, Boston, Nov. 1997.
R. Marée, P. Geurts, and L. Wehenkel, "Content-based image retrieval by indexing random subwindows with randomized trees," IPSJ Transactions on Computer Vision and Applications. To appear., 2009, extended version of ACCV 2007 paper.
M. Dumont, R. Marée, L. Wehenkel, and P. Geurts, "Fast multi-class image annotation with random subwindows and multiple output randomized trees," in Proc. International Conference on Computer Vision Theory and Applications (VISAPP), Feb 2009.