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Design of embedded digital image processing system based on ZYNQ

机译:基于Zynq的嵌入式数字图像处理系统设计

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Zynq- real time edge detection system based on execution of the image reconstructed from the sequence. Although the object edge detection is an essential tool in computer vision, edge detection results in the negative image frame noise significantly. Further, due to the high computational complexity of an image filtering operation, implemented in the hardware configuration of the re-configurable hardware it is necessary. In this portion, the proposed dynamic Zynq embedded system reconfiguration capability to detect according to the input image frame to the noise level of the different density filters perform during runtime bit stream re Configuration.The results show that the accuracy of edge detection is highly evaluated. We analyze various noise density levels, and the results show that the edge detection results of the proposed filter bit stream are more accurate, while effectively providing computing capacity to support the real-time processing of the image frame. In the configuration time, CPU usage, and hardware resource utilization performance test results were compared.
机译:Zynq-实时边缘检测系统基于从序列重建的图像的执行。虽然对象边缘检测是计算机视觉中的必备工具,但边缘检测显着导致负图像帧噪声。此外,由于图像滤波操作的高计算复杂性,在重新配置硬件的硬件配置中实现是必要的。在该部分中,所提出的动态Zynq嵌入式系统重配置能力以根据输入图像帧检测到不同密度滤波器的噪声电平,在运行时比特流重新配置期间执行。结果表明高度评估了边缘检测的准确性。我们分析了各种噪声密度水平,结果表明,所提出的滤波器比特流的边缘检测结果更准确,同时有效地提供计算容量来支持图像帧的实时处理。在配置时间,CPU使用率和硬件资源利用性能测试结果中进行了比较。

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