Performance Evaluation of Real-Time Video Processing Edge Detection on Various Platforms

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Institute of Electrical and Electronics Engineers Inc.

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info:eu-repo/semantics/closedAccess

Özet

As real-time video processing applications grow in complexity, they demand higher performance. Achieving such a performance must involve a delicate balance between design constraints and optimization of performance criteria. A vital aspect of this balance is the integration of application-specific accelerator designs to boost computational efficiency. To illustrate this, we applied Laplacian High-Pass filtering operations on real-time video signals across three hardware platforms an ARM processor, an ARM+FPGA-based SoC, and a single-core Intel i7 processor. We further analyzed these platforms' price-performance ratios. Our research revealed that the ARM+FPGA-based SoC executed the filtering algorithms 23.124 times faster than the ARM processor and 1.969 times faster than the Intel i7 processor. Additionally, the ARM+FPGA-based SoC also showed the highest price-performance efficiency. To offer readers a more visual understanding, we include a resource utilization graph for the SoC hardware accelerator development board, thus demonstrating the efficiency of each platform tested. © 2023 Elsevier B.V., All rights reserved.

Açıklama

17th IEEE International Conference on Application of Information and Communication Technologies, AICT 2023 -- Baku -- 194482

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FPGA Vision, Hardware accelerator, OpenCV, Overlay design, Pipeline architecture, PYNQ-Z1 SoC, Video processing

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