Paper
24 May 1996 Fusion of focus of attention alternatives for FLIR imagery
Terry A. Wilson, Steven K. Rogers, Randy P. Broussard, Thomas F. Rathbun
Author Affiliations +
Abstract
A model-based vision (MBV) approach to automatic target cuing/recognition (ATC/R) using real infrared (IR) image data will be presented. The MBV-ATC/R is comprised of three parts: Focus of attention (FOA), indexing, and match/search. The FOA module analyzes the IR image and extracts (segments) regions of interest that may contain targets. The focus of this article will be on the FOA portion of the MBV-ATC/R approach. In particular, three methods of FOA will be optimized, compared, and fused. The first FOA module is a Least Asymmetrical Daubechies wavelet decomposition method. The second FOA module is a physiologically based Difference of Gaussians. The third FOA module is a Morphological hit- and-miss transform. The three FOA algorithms are individually optimized using a genetic algorithm. Then an adaptive pulse coupled neural network is used to fuse the results.
© (1996) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Terry A. Wilson, Steven K. Rogers, Randy P. Broussard, and Thomas F. Rathbun "Fusion of focus of attention alternatives for FLIR imagery", Proc. SPIE 2756, Automatic Object Recognition VI, (24 May 1996); https://doi.org/10.1117/12.241135
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Cited by 1 scholarly publication.
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KEYWORDS
Image filtering

Image fusion

Neurons

Wavelets

Image processing

Target detection

Detection and tracking algorithms

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