Embedded Video and Image Processing using ARM based FPGA

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2014
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Swarthmore College. Dept. of Engineering
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Thesis (B.A.)
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Full copyright to this work is retained by the student author. It may only be used for non-commercial, research, and educational purposes. All other uses are restricted.
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Abstract
To meet the demands of the real-time video and image processing (VIP) applications, Field Programmable Gate Array (FPGA) is considered as one of the ideal system architectures for implementation. It is because the customizable hardware of FPGA offers much higher performance than the software-only approaches using microprocessor or DSP. There is a new breed of System-on-Chip (SoC) FPGA which embeds a dual-core ARM processor with FPGA hardware. Combining the benefits of FPGA hardware and CPU programmability, such an SoC FPGA can not only provide parallelization and program speedup that the traditional CPUs computational ability typically prevents, but also offer software intelligence to increase the ease and flexibility to implement complex computational algorithms. The objectives of this project include the understanding of the multitude of the development system for SoC FPGA and how to utilize it for VIP applications. The culmination of our project is a runtime comparison of a picture-in-picture video image application on the SoC FPGA versus the software-only implementation on CPU via OpenCV's Python platform. The experimental results show that SoC FPGA implementation run about 3000 times faster in moving a picture-in-picture application than a software-only implementation.
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