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Automatic target recognition performance losses in the presence of atmospheric and camera effects

[+] Author Affiliations
Xiaohan Chen

West Virginia University, Lane Department of Computer Science and Electrical Engineering, Morgantown, West Virginia 26506

Natalia A. Schmid

West Virginia University, Lane Department of Computer Science and Electrical Engineering, Morgantown, West Virginia 26506

J. Electron. Imaging. 19(2), 023016 (June 01, 2010). doi:10.1117/1.3435348
History: Received August 27, 2009; Revised April 12, 2010; Accepted April 19, 2010; Published June 01, 2010; Online June 01, 2010
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The importance of networked automatic target recognition systems for surveillance applications is continuously increasing. Because of the requirement of a low cost and limited payload, these networks are traditionally equipped with lightweight, low-cost sensors such as electro-optical (EO) or infrared sensors. The quality of imagery acquired by these sensors critically depends on the environmental conditions, type and characteristics of sensors, and absence of occluding or concealing objects. In the past, a large number of efficient detection, tracking, and recognition algorithms have been designed to operate on imagery of good quality. However, detection and recognition limits under nonideal environmental and/or sensor-based distortions have not been carefully evaluated. We introduce a fully automatic target recognition system that involves a Haar-based detector to select potential regions of interest within images, performs adjustment of detected regions, segments potential targets using a region-based approach, identifies targets using Bessel K form–based encoding, and performs clutter rejection. We investigate the effects of environmental and camera conditions on target detection and recognition performance. Two databases are involved. One is a simulated database generated using a 3-D tool. The other database is formed by imaging 10 die-cast models of military vehicles from different elevation and orientation angles. The database contains imagery acquired both indoors and outdoors. The indoors data set is composed of clear and distorted images. The distortions include defocus blur, sided illumination, low contrast, shadows, and occlusions. All images in this database, however, have a uniform (blue) background. The indoors database is applied to evaluate the degradations of recognition performance due to camera and illumination effects. The database collected outdoors includes a real background and is much more complex to process. The numerical results demonstrate that the complexity of the background and the presence of occlusions present a serious challenge for automatic target detection and recognition.

© 2010 SPIE and IS&T

Citation

Xiaohan Chen and Natalia A. Schmid
"Automatic target recognition performance losses in the presence of atmospheric and camera effects", J. Electron. Imaging. 19(2), 023016 (June 01, 2010). ; http://dx.doi.org/10.1117/1.3435348


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