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 | 2023-12-22T07:20:52Z | |
| dc.date.available | 2023-12-22T07:20:52Z | |
| dc.date.issued | 2023 | en_US |
| dc.department | FSM Vakıf Üniversitesi, Mühendislik Fakültesi, Elektrik-Elektronik Mühendisliği Bölümü | en_US |
| 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’ 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. | en_US |
| dc.identifier.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). | en_US |
| dc.identifier.doi | 10.1109/AICT59525.2023.10313150 | |
| dc.identifier.orcid | https://orcid.org/0000-0002-3664-1366 | en_US |
| dc.identifier.orcid | https://orcid.org/0000-0002-4600-1880 | en_US |
| dc.identifier.orcid | https://orcid.org/0000-0002-7881-1263 | en_US |
| dc.identifier.scopus | 2-s2.0-85179517165 | |
| dc.identifier.scopusquality | N/A | |
| dc.identifier.uri | https://hdl.handle.net/11352/4690 | |
| dc.indekslendigikaynak | Scopus | |
| dc.institutionauthor | Tatar, Güner | |
| dc.language.iso | en | |
| dc.publisher | IEEE | en_US |
| dc.relation.ispartof | 2023 IEEE 17th International Conference on Application of Information and Communication Technologies (AICT) | |
| dc.relation.publicationcategory | Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı | en_US |
| dc.rights | info:eu-repo/semantics/embargoedAccess | en_US |
| dc.subject | Video Processing | en_US |
| dc.subject | OpenCV | en_US |
| dc.subject | PYNQ-Z1 SoC | en_US |
| dc.subject | FPGA Vision | en_US |
| dc.subject | Overlay Design | en_US |
| dc.subject | Pipeline Architecture | en_US |
| dc.subject | Hardware Accelerator | en_US |
| dc.title | Performance Evaluation of Real-Time Video Processing Edge Detection on Various Platforms | en_US |
| dc.type | Conference Object |










