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dc.contributor.authorTatar, Güner
dc.contributor.authorBayar, Salih
dc.contributor.authorÇiçek, İhsan
dc.date.accessioned2023-12-22T07:20:52Z
dc.date.available2023-12-22T07:20:52Z
dc.date.issued2023en_US
dc.identifier.citationTATAR, 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.urihttps://hdl.handle.net/11352/4690
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’ 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.language.isoengen_US
dc.publisherIEEEen_US
dc.relation.isversionof10.1109/AICT59525.2023.10313150en_US
dc.rightsinfo:eu-repo/semantics/embargoedAccessen_US
dc.subjectVideo Processingen_US
dc.subjectOpenCVen_US
dc.subjectPYNQ-Z1 SoCen_US
dc.subjectFPGA Visionen_US
dc.subjectOverlay Designen_US
dc.subjectPipeline Architectureen_US
dc.subjectHardware Acceleratoren_US
dc.titlePerformance Evaluation of Real-Time Video Processing Edge Detection on Various Platformsen_US
dc.typeconferenceObjecten_US
dc.relation.journal2023 IEEE 17th International Conference on Application of Information and Communication Technologies (AICT)en_US
dc.contributor.departmentFSM Vakıf Üniversitesi, Mühendislik Fakültesi, Elektrik-Elektronik Mühendisliği Bölümüen_US
dc.contributor.authorIDhttps://orcid.org/0000-0002-3664-1366en_US
dc.contributor.authorIDhttps://orcid.org/0000-0002-4600-1880en_US
dc.contributor.authorIDhttps://orcid.org/0000-0002-7881-1263en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.contributor.institutionauthorTatar, Güner


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