By Ikuko Mitsuoka
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In this case, narrowing down the area of interest helped to reduce the amount of data to be processed by the subpixel refinement stage, thus generating a real-time subpixel accurate object detection. Similarly, in another application involving the use of range data for gesture tracking , the range data was calculated only for selected regions of interest and not for the entire image. Therefore, if computationally complex processing cannot be avoided to save processing time, it is best to apply such processing only to the areas of interest and not to the entire image.
In essence, FPGAs have high computational and memory bandwidth capabilities that are essential to real-time image/video processing systems. Because of such features, there has been an increasing interest in using FPGAs to solve real-time image/video processing problems . FPGAs have already been used to solve many practical real-world, real-time image/video processing problems, from a preprocessing component to the entire processing chain. FPGAs have also been used in conjunction with DSPs. A current trend in FPGAs is to include a GPP core on the same chip as the FPGA for a customizable system-on-chip (SoC) solution.
2 FPGA-Based Systems Due to their flexibility in implementing custom hardware solutions, FPGAs have been used extensively for implementing a single component of an image or video processing system all the way up to the entire system. The main reason often cited for using FPGAs over other platforms is that they provide a low-cost, flexible development of high-performance, custom parallel processors, suitable for transitioning almost any kind of image/video processing algorithm from a development environment to a real-time implementation.