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Real-time video edge detection with the memory access improvement

机译:实时视频边缘检测,内存访问得到改善

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Real-time video processing is the basic requirement for applications such as video surveillance, traffic management and medical imaging. The high computation power is a requirement to support this operation. This requirement could be fulfilled by utilizing the hardware accelerator architecture for computation part. This paper presents the development of edge detection hardware accelerator architecture for real time video processing systems. The algorithm of Sobel edge detection operator is used to develop this hardware accelerator. The NTSC standard definition video is digitized at 720×480 with a video rate of 30 frames per second. To develop hardware accelerator datapath architecture the management of memory access is deployed and architecture based pipeline are made with the potential of improvements in acceleration to read the data pixel from memory. In addition, a finite state machine is used to ensure the hardware accelerator controls the sequence of derivative computation, write and read operations. Initial simulation shows that the hardware accelerator architecture manages to achieve approximately 75% memory bandwidth reduction compare to previous work [5].
机译:实时视频处理是视频监控,交通管理和医学成像等应用的基本要求。高计算能力是支持此操作的要求。通过使用硬件加速器体系结构的计算部分可以满足此要求。本文介绍了用于实时视频处理系统的边缘检测硬件加速器体系结构的开发。 Sobel边缘检测算子的算法用于开发此硬件加速器。 NTSC标清视频以720×480的速率数字化,每秒30帧的视频速率。为了开发硬件加速器数据路径体系结构,部署了内存访问管理,并建立了基于体系结构的流水线,具有改善从存储器读取数据像素的加速潜力。另外,使用有限状态机来确保硬件加速器控制导数计算,写入和读取操作的顺序。初步仿真显示,与先前的工作相比,硬件加速器体系结构设法实现了大约75%的内存带宽减少[5]。

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