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The image/video processing and computer vision algorithms are crucial mechanisms of many manufacturing, bio-medical, and research-related applications. Recent image processing system offers high definition (HD) images at high frame rates; to process this image data complex computations are required. Conversely, in several applications rapid processing is needed. Central Processing Unit (CPU) is insufficient to perform these type of applications, as they accomplish the computations with insufficient speed. To minimize the computational time and increasing the processing speed, algorithms can be implemented on hardware accelerators like field-programmable gate arrays (FPGAs). While hardware implementation of image processing algorithms designer will face a lot of problems (type of FPGA used, available tools, ways of implementing the algorithms). Along with the implementation of the Sobel edge detection on zynq-702 all programmable FPGA, the above-mentioned concerns are addressed.
Soma et al. (2018) studied this question.