Hierarchical multifeature integration for automatic target recognition

Shishir Shah; Jake K. Aggarwal

doi:10.1117/12.357176

27 July 1999 Hierarchical multifeature integration for automatic target recognition

Shishir Shah, Jake K. Aggarwal

Proceedings Volume 3720, Signal Processing, Sensor Fusion, and Target Recognition VIII; (1999) https://doi.org/10.1117/12.357176
Event: AeroSense '99, 1999, Orlando, FL, United States

Abstract

This paper presents a methodology for object recognition in complex scenes by learning multiple feature object representation in second generation Forward Looking InfraRed (FLIR) images. A hierarchical recognition framework is developed which solves the recognition task by performing classification using decisions at the lower levels and the input features. The system uses new algorithms for detection and segmentation of objects and a Bayesian formulation for combining multiple object features for improved discrimination. Experimental results on a large database of FLIR images is presented to validate the robustness of the system, and its applicability to FLIR imagery obtained from real scenes.

Citation Download Citation

Shishir Shah and Jake K. Aggarwal "Hierarchical multifeature integration for automatic target recognition", Proc. SPIE 3720, Signal Processing, Sensor Fusion, and Target Recognition VIII, (27 July 1999); https://doi.org/10.1117/12.357176

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available