1 August 2007 New two-stage correlation-based approach for target detection and tracking in forward-looking infrared imagery using filters based on extended maximum average correlation height and polynomial distance classifier correlation
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Optical Engineering, 46(8), 086401 (2007). doi:10.1117/1.2769648
Abstract
A novel approach is proposed to recognize and track multiple identical and/or dissimilar targets in forward-looking infrared (FLIR) image sequences using a combination of an extended maximum average correlation height (EMACH) filter and polynomial distance classifier correlation filter (PDCCF). The EMACH filter and PDCCF are trained a priori using representative training images of targets with expected size and orientation variations. In the first step, the input scene is correlated with all EMACH filters (one for each desired or expected target class). Based on the regions with higher correlation peak values in the combined correlation output, a sufficient number of regions of interest (ROIs) are selected from the input scene. In the second step, a PDCCF is applied to these ROIs to identify target types and reject clutter and background. Moving-target detection and tracking is accomplished by applying this technique independently to all incoming image frames. Independent tracking of target(s) from one frame to the other allows the system to handle complicated situations such as a target disappearing in a few frames and then reappearing in later frames. This method yields robust performance for challenging FLIR imagery in terms of accurate detection and classification as well as tracking of the targets.
Sharif Md. Ataullah Bhuiyan, Mohammad S. Alam, Mohamed I. Alkanhal, "New two-stage correlation-based approach for target detection and tracking in forward-looking infrared imagery using filters based on extended maximum average correlation height and polynomial distance classifier correlation," Optical Engineering 46(8), 086401 (1 August 2007). http://dx.doi.org/10.1117/1.2769648
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KEYWORDS
Target detection

Image filtering

Detection and tracking algorithms

Forward looking infrared

Optical filters

Image classification

Optical engineering

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