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Optical Engineering

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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Paper 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.

Paper Details

Date Published: 1 August 2007
PDF: 14 pages
Opt. Eng. 46(8) 086401 doi: 10.1117/1.2769648
Published in: Optical Engineering Volume 46, Issue 8
Show Author Affiliations
Sharif Md. Ataullah Bhuiyan, Univ. of South Alabama (United States)
Mohammad S. Alam, Univ. of South Alabama (United States)
Mohamed I. Alkanhal, King Abdulaziz City for Science & Technology (Saudi Arabia)


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