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Real-time video edge detection with the memory access improvement

机译:实时视频边缘检测与内存访问改进

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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。可以利用用于计算部分的硬件加速器架构来满足该要求。本文提出了用于实时视频处理系统的边缘检测硬件加速器架构的开发。 Sobel边缘检测操作员的算法用于开发此硬件加速器。 NTSC标准定义视频以720×480数字化,视频速率为每秒30帧。要开发硬件加速器数据架构,可以部署内存访问的管理,并且基于架构的流水线进行了加速度的改进,以读取来自存储器的数据像素。此外,使用有限状态机器来确保硬件加速器控制衍生计算,写入和读取操作的序列。初始仿真显示硬件加速器架构管理以实现与上一个工作[5]比较大约75%的内存带宽减少。

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