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Real-time hardware-software embedded vision system for ITS smart camera implemented in Zynq SoC

机译:在Zynq SoC中实现的用于ITS智能相机的实时软硬件嵌入式视觉系统

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The article demonstrates the usefulness of heterogeneous System on Chip (SoC) devices in smart cameras used in intelligent transportation systems (ITS). In a compact, energy efficient system the following exemplary algorithms were implemented: vehicle queue length estimation, vehicle detection, vehicle counting and speed estimation (using multiple virtual detection lines), as well as vehicle type (local binary features and SVM classifier) and colour (k-means classifier and YCbCr colourspace analysis) recognition. The solution exploits the hardware–software architecture, i.e. the combination of reconfigurable resources and the efficient ARM processor. Most of the modules were implemented in hardware, using Verilog HDL, taking full advantage of the possible parallelization and pipeline, which allowed to obtain real-time image processing. The ARM processor is responsible for executing some parts of the algorithm, i.e. high-level image processing and analysis, as well as for communication with the external systems (e.g. traffic lights controllers). The demonstrated results indicate that modern SoC systems are a very interesting platform for advanced ITS systems and other advanced embedded image processing, analysis and recognition applications.
机译:本文演示了异构系统芯片(SoC)设备在智能交通系统(ITS)中使用的智能相机中的有用性。在紧凑的节能系统中,实现了以下示例性算法:车辆队列长度估计,车辆检测,车辆计数和速度估计(使用多个虚拟检测线)以及车辆类型(本地二进制特征和SVM分类器)和颜色(k均值分类器和YCbCr色彩空间分析)识别。该解决方案利用了硬件-软件体系结构,即可重新配置的资源和高效的ARM处理器的组合。大多数模块都是使用Verilog HDL在硬件中实现的,充分利用了可能的并行化和流水线技术,从而可以获取实时图像处理。 ARM处理器负责执行算法的某些部分,即高级图像处理和分析,并负责与外部系统(例如交通信号灯控制器)的通信。演示的结果表明,现代SoC系统对于高级ITS系统以及其他高级嵌入式图像处理,分析和识别应用程序来说是一个非常有趣的平台。

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