Publication: Performance evaluation of real-time video processing edge detection on various platforms
| dc.contributor.author | BAYAR, SALİH | |
| dc.contributor.authors | TATAR G., BAYAR S., ÇİÇEK İ. | |
| dc.date.accessioned | 2023-12-11T09:18:56Z | |
| dc.date.accessioned | 2026-01-10T17:23:03Z | |
| dc.date.available | 2023-12-11T09:18:56Z | |
| dc.date.issued | 2023-11-13 | |
| dc.description.abstract | 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. | |
| dc.identifier.citation | TATAR G., BAYAR S., ÇİÇEK İ., \"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), 18 - 20 Ekim 2023 | |
| dc.identifier.doi | 10.1109/aict59525.2023.10313150 | |
| dc.identifier.uri | http://dx.doi.org/10.1109/aict59525.2023.10313150 | |
| dc.identifier.uri | https://hdl.handle.net/11424/295542 | |
| dc.language.iso | eng | |
| dc.relation.ispartof | 2023 IEEE 17th International Conference on Application of Information and Communication Technologies (AICT) | |
| dc.rights | info:eu-repo/semantics/openAccess | |
| dc.subject | Video processing | |
| dc.subject | OpenCV | |
| dc.subject | PYNQ-Z1 SoC | |
| dc.subject | FPGA Vision | |
| dc.subject | Overlay design | |
| dc.subject | Pipeline architecture | |
| dc.subject | Hardware accelerator | |
| dc.title | Performance evaluation of real-time video processing edge detection on various platforms | |
| dc.type | conferenceObject | |
| dspace.entity.type | Publication |
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