Abstract
Template matching techniques are widely used today in image-based tracking systems to identify and track military targets. Due to their passivity, these systems are resistant to common electronic warfare techniques. One of the problems with using template matching algorithms is that they are slow, especially when rotation and scaling occur in targets relative to a predetermined pattern. In this paper, we perform an optimized algorithm for grayscale template-matching based on correlation coefficients which is invariant to scale and angle. The ‘brute force’ algorithm performs template-matching between the image to analyze and the template query shape rotated by specific angle, translated to specific scale. This takes too long and thus is no practical. The optimized algorithm includes three cascaded filters for scale, angle and template matching which results in probability of scaling, rotated angle for each pixel and point of template-matching, respectively. This algorithm accelerates searching and is 400 times faster than ‘Brute Force’ algorithm. By implementing hardware on the FPGA, it is possible to identify and track military targets at a speed of 10 frames per second.
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