Dynamic Vergence Using Log-Polar Images
International Journal of Computer Vision
A review of biologically motivated space-variant data reduction models for robotic vision
Computer Vision and Image Understanding
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Log-polar or spatially variant image representation is an important component of active vision system in tracking process for many robotic applications due to its data compression ability, faster sampling rates and hence, direct to faster image-processing speed in machine vision system. In this paper, we try to implement log-polar mapping techniques on Xilinx FPGA (Field Programmable Gate Array) board for unwarping the omnidirectional images into panoramic images to present a wide angle of view by preserving fine output image quality in a higher data compression manner. Simulations are also run on MATLAB to find out the optimum mapping criterion. Some significant advantages of this new approach are: lighter processing system, lesser space utilisation, cost saving, faster processing speed and faster reset time (boot time) compared to a laptop computer that uses MATLAB for doing the unwarping process.