Co-design and Implementation of Image Recognition Based on ARM and FPGA
With the development of the Internet of things, the image recognition system is widely required in many fields. It has very high requirement in real-time, but usually it has high complexity and large data. So the real-time, which improved by hardware acceleration, is the key of image recognition system. Traditional processors have the disadvantages of low flexibility and configurability for prototype of embedded system. The family of Xilinx Zynq7000 processors integrate dual-core ARM Cortext-A9 and low-power FPGA. It can improve the operating efficiency and dynamical configurability of developing image applications. It also can reduce the power consumption of image processing. In this paper, we present an ARM and FPGA Co-design architecture of image recognition system based on Zynq7000 processor. Then we validate this architecture by the leaf recognition system. This architecture is based on module designed at system-level and modeled at algorithm-level. After determining the algorithm option, we partite the ARM and FPGA of modules depending on algorithm simulation, and then implement them separately. Finally, ARM and FPGA modules are interconnected by interface or driver. When the joint debugging is completed, prototype development of the embedded application is finished. As the experiment shown, FPGA and ARM co-design is 1.84 times faster than the pure ARM.
KeywordsCo-design and implementation ARM + FPGA Image recognition
This work is partially sponsored by Natural Science Foundation of Shanghai (15ZR1410000).
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