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Proceedings Paper

Automatic parameter adjustment of difference of Gaussian (DoG) filter to improve OT-MACH filter performance for target recognition applications
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Paper Abstract

A wavelet-modified frequency domain Optimal Trade-off Maximum Average Correlation Height (OT-MACH) filter has been trained using 3D CAD models and tested on real target images acquired from a Forward Looking Infra Red (FLIR) sensor. The OT-MACH filter can be used to detect and discriminate predefined targets from a cluttered background. The FLIR sensor extends the filter's ability by increasing the range of detection by exploiting the heat signature differences between the target and the background. A Difference of Gaussians (DoG) based wavelet filter has been use to improve the OT-MACH filter discrimination ability and distortion tolerance. Choosing the right standard deviation values of the two Gaussians comprising the filter is critical. In this paper we present a new technique for auto adjustment of the DoG filter parameters driven by the expected target size. Tests were carried on images acquired by the Apache AH-64 helicopter mounted FLIR sensor, results showing an overall improvement in the recognition of target objects present within the IR images.

Paper Details

Date Published: 28 September 2011
PDF: 8 pages
Proc. SPIE 8185, Electro-Optical and Infrared Systems: Technology and Applications VIII, 81850M (28 September 2011); doi: 10.1117/12.897309
Show Author Affiliations
Ahmad Alkandri, Univ. of Sussex (United Kingdom)
Akber Gardezi, Univ. of Sussex (United Kingdom)
Nagachetan Bangalore, Univ. of Sussex (United Kingdom)
Philip Birch, Univ. of Sussex (United Kingdom)
Rupert Young, Univ. of Sussex (United Kingdom)
Chris Chatwin, Univ. of Sussex (United Kingdom)

Published in SPIE Proceedings Vol. 8185:
Electro-Optical and Infrared Systems: Technology and Applications VIII
David A. Huckridge; Reinhard R. Ebert, Editor(s)

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