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26 April 2011Enhancement of the speed of space-variant correlation filter
implementations by using low-pass pre-filtering for kernel placement
and applications to real-time security monitoring
A space domain implementation of the Optimal Trade-off Maximum Average Correlation Height (OT-MACH) filter can
not only be designed to be invariant to change in orientation of the target object but also to be spatially variant, i.e. the
filter function becoming dependant on local clutter conditions within the image. Sequential location of the kernel in all
regions of the image does, however, require excessive computational resources. An optimization technique is discussed
in this paper which employs low-pass filtering to highlight the potential region of interests in the image and then restricts
the movement of the kernel to these regions to allow target identification. The detection and subsequent identification
capability of the two-stage process has been evaluated in highly cluttered backgrounds using both visible and thermal
imagery and associated training data sets. A performance matrix comprised of peak-to-correlation energy (PCE) and
peak-to-side lobe ratio (PSR) measurements of the correlation output has been calculated to allow the definition of a
recognition criterion. A feasible hardware implementation for potential use in a security application using the proposed
two-stage process is also described in the paper.
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Akber Gardezi, Ahmad Al-Kandri, Philip Birch, Rupert Young, Chris Chatwin, "Enhancement of the speed of space-variant correlation filter implementations by using low-pass pre-filtering for kernel placement and applications to real-time security monitoring," Proc. SPIE 8055, Optical Pattern Recognition XXII, 805509 (26 April 2011); https://doi.org/10.1117/12.883784