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

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info:eu-repo/semantics/embargoedAccess

Date

2023

Author

Tatar, Güner
Bayar, Salih
Çiçek, İhsan

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Citation

TATAR, Güner, Salih BAYAR & İhsan ÇİÇEK. "Performance Evaluation of Real-Time Video Processing Edge Detection on Various Platforms". 2023 IEEE 17th International Conference on Application of Information and Communication Technologies (AICT), (2023).

Abstract

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’ priceperformance ratios. Our research revealed that the ARM+FPGAbased 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.

Source

2023 IEEE 17th International Conference on Application of Information and Communication Technologies (AICT)

URI

https://hdl.handle.net/11352/4690

Collections

  • Elektrik-Elektronik Mühendisliği Bölümü [75]
  • Scopus İndeksli Yayınlar / Scopus Indexed Publications [756]



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