Performance Evaluation of Real-Time Video Processing Edge Detection on Various Platforms
| dc.contributor.author | Tatar, Güner | |
| dc.contributor.author | Bayar, Salih | |
| dc.contributor.author | ÇiÇek, İhsan | |
| dc.date.accessioned | 2025-10-29T12:08:09Z | |
| dc.date.issued | 2023 | |
| dc.department | Fakülteler, Mühendislik Fakültesi, Elektronik Mühendisliği Bölümü | |
| dc.description | 17th IEEE International Conference on Application of Information and Communication Technologies, AICT 2023 -- Baku -- 194482 | |
| dc.description.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' 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. | |
| dc.identifier.doi | 10.1109/AICT59525.2023.10313150 | |
| dc.identifier.isbn | 9798350303568 | |
| dc.identifier.scopus | 2-s2.0-85179517165 | |
| dc.identifier.scopusquality | N/A | |
| dc.identifier.uri | https://doi.org/10.1109/AICT59525.2023.10313150 | |
| dc.identifier.uri | https://hdl.handle.net/20.500.14854/14317 | |
| dc.indekslendigikaynak | Scopus | |
| dc.language.iso | en | |
| dc.publisher | Institute of Electrical and Electronics Engineers Inc. | |
| dc.relation.publicationcategory | Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı | |
| dc.rights | info:eu-repo/semantics/closedAccess | |
| dc.snmz | KA_Scopus_20251020 | |
| dc.subject | FPGA Vision | |
| dc.subject | Hardware accelerator | |
| dc.subject | OpenCV | |
| dc.subject | Overlay design | |
| dc.subject | Pipeline architecture | |
| dc.subject | PYNQ-Z1 SoC | |
| dc.subject | Video processing | |
| dc.title | Performance Evaluation of Real-Time Video Processing Edge Detection on Various Platforms | |
| dc.type | Conference Object |








