{"title":"硬件加速器边缘检测","authors":"Aous H. Kurdi, J. Grantner, I. Abdel-Qader","doi":"10.1109/INES49302.2020.9147174","DOIUrl":null,"url":null,"abstract":"Hardware accelerators have been recently proposed for computationally extensive applications like real-time video image processing systems. Contemporary hardware accelerators are implemented by using either Field Programmable Gate Array (FPGA) or System-on-Chip (SoC) devices. Edge detection is a fundamental task for any image processing system. In this paper, a pipelined architecture for a fuzzy logic edge detection system is proposed. The system has been implemented and tested on various Xilinx 7 Series devices. The hardware accelerator core utilizes a pipeline of seven stages. Depending on the available resources the accelerator system can be made up of several cores operating simultaneously. A single-core implementation of the system can process a 1080P HD test frame at a rate of about 45 frames per second. It outperforms its software counterpart by a factor of ten thousand.","PeriodicalId":175830,"journal":{"name":"2020 IEEE 24th International Conference on Intelligent Engineering Systems (INES)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Hardware Accelerator for Edge Detection\",\"authors\":\"Aous H. Kurdi, J. Grantner, I. Abdel-Qader\",\"doi\":\"10.1109/INES49302.2020.9147174\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Hardware accelerators have been recently proposed for computationally extensive applications like real-time video image processing systems. Contemporary hardware accelerators are implemented by using either Field Programmable Gate Array (FPGA) or System-on-Chip (SoC) devices. Edge detection is a fundamental task for any image processing system. In this paper, a pipelined architecture for a fuzzy logic edge detection system is proposed. The system has been implemented and tested on various Xilinx 7 Series devices. The hardware accelerator core utilizes a pipeline of seven stages. Depending on the available resources the accelerator system can be made up of several cores operating simultaneously. A single-core implementation of the system can process a 1080P HD test frame at a rate of about 45 frames per second. It outperforms its software counterpart by a factor of ten thousand.\",\"PeriodicalId\":175830,\"journal\":{\"name\":\"2020 IEEE 24th International Conference on Intelligent Engineering Systems (INES)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 IEEE 24th International Conference on Intelligent Engineering Systems (INES)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/INES49302.2020.9147174\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE 24th International Conference on Intelligent Engineering Systems (INES)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/INES49302.2020.9147174","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Hardware accelerators have been recently proposed for computationally extensive applications like real-time video image processing systems. Contemporary hardware accelerators are implemented by using either Field Programmable Gate Array (FPGA) or System-on-Chip (SoC) devices. Edge detection is a fundamental task for any image processing system. In this paper, a pipelined architecture for a fuzzy logic edge detection system is proposed. The system has been implemented and tested on various Xilinx 7 Series devices. The hardware accelerator core utilizes a pipeline of seven stages. Depending on the available resources the accelerator system can be made up of several cores operating simultaneously. A single-core implementation of the system can process a 1080P HD test frame at a rate of about 45 frames per second. It outperforms its software counterpart by a factor of ten thousand.