Publication:
Performance evaluation of real-time video processing edge detection on various platforms

dc.contributor.authorBAYAR, SALİH
dc.contributor.authorsTATAR G., BAYAR S., ÇİÇEK İ.
dc.date.accessioned2023-12-11T09:18:56Z
dc.date.accessioned2026-01-10T17:23:03Z
dc.date.available2023-12-11T09:18:56Z
dc.date.issued2023-11-13
dc.description.abstractAbstract—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.citationTATAR 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.doi10.1109/aict59525.2023.10313150
dc.identifier.urihttp://dx.doi.org/10.1109/aict59525.2023.10313150
dc.identifier.urihttps://hdl.handle.net/11424/295542
dc.language.isoeng
dc.relation.ispartof2023 IEEE 17th International Conference on Application of Information and Communication Technologies (AICT)
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectVideo processing
dc.subjectOpenCV
dc.subjectPYNQ-Z1 SoC
dc.subjectFPGA Vision
dc.subjectOverlay design
dc.subjectPipeline architecture
dc.subjectHardware accelerator
dc.titlePerformance evaluation of real-time video processing edge detection on various platforms
dc.typeconferenceObject
dspace.entity.typePublication

Files

Original bundle

Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
file.pdf
Size:
5.39 MB
Format:
Adobe Portable Document Format