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

dc.contributor.authorTatar, Güner
dc.contributor.authorBayar, Salih
dc.contributor.authorÇiÇek, İhsan
dc.date.accessioned2025-10-29T12:08:09Z
dc.date.issued2023
dc.departmentFakülteler, Mühendislik Fakültesi, Elektronik Mühendisliği Bölümü
dc.description17th IEEE International Conference on Application of Information and Communication Technologies, AICT 2023 -- Baku -- 194482
dc.description.abstractAs 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.doi10.1109/AICT59525.2023.10313150
dc.identifier.isbn9798350303568
dc.identifier.scopus2-s2.0-85179517165
dc.identifier.scopusqualityN/A
dc.identifier.urihttps://doi.org/10.1109/AICT59525.2023.10313150
dc.identifier.urihttps://hdl.handle.net/20.500.14854/14317
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_Scopus_20251020
dc.subjectFPGA Vision
dc.subjectHardware accelerator
dc.subjectOpenCV
dc.subjectOverlay design
dc.subjectPipeline architecture
dc.subjectPYNQ-Z1 SoC
dc.subjectVideo processing
dc.titlePerformance Evaluation of Real-Time Video Processing Edge Detection on Various Platforms
dc.typeConference Object

Dosyalar