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Implementation of real time moving object detection and tracking on FPGA for video surveillance applications

机译:用于视频监控应用的FPGA上实时运动目标检测和跟踪的实现

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Computer vision has played a key role in developing object detection and tracking techniques for Surveillance system. Most of the implementations currently employed are based on Serial execution on General Purpose Processors. But the high cost and complexity of such implementations doesn't make it a viable option for real time surveillance system. The system proposed here is implemented on Field Programmable Gate Arrays (FPGA) Zynq XC7Z020 board using Modified Background Subtraction algorithm for real-time Object Detection and Tracking. The presence of numerous configurable logic blocks, distributed memory and hard Digital Signal Processing (DSP) modules offers a great flexibility in achieving Temporal and Spatial parallelism. This paper uses Xilinx ISE software for implementation which is programmed in VHDL. OV7670 camera used in the paper has a resolution of 0.3 Megapixel and it captures the video at a speed of 30fps. The reference frame and the subsequent incoming frames are stored in different memory modules before the Modified Background Subtraction algorithm is applied on these frames to obtain the difference image. After comparing it with the threshold, the resultant image is displayed and its addresses are stored in order to track it. The system works in real time with minimum time lag between the capture and display. Moreover the entire system is optimized in terms of speed, memory requirements as well as the number of logic elements used which makes it suitable for application in real-time surveillance system.
机译:计算机视觉在开发监视系统的对象检测和跟踪技术方面发挥了关键作用。当前采用的大多数实现都是基于通用处理器上的串行执行。但是,这种实现方式的高成本和复杂性并不能使其成为实时监控系统的可行选择。此处提出的系统是在现场可编程门阵列(FPGA)Zynq XC7Z020板上实现的,该系统使用改进的背景扣除算法进行实时对象检测和跟踪。大量可配置逻辑块,分布式存储器和硬数字信号处理(DSP)模块的存在为实现时空并行提供了极大的灵活性。本文使用在VHDL中编程的Xilinx ISE软件进行实施。本文中使用的OV7670摄像机的分辨率为0.3兆像素,并以30fps的速度捕获视频。在将修改后的背景减除算法应用于这些帧以获得差异图像之前,参考帧和随后的传入帧将存储在不同的存储模块中。在将其与阈值进行比较之后,将显示结果图像并存储其地址以进行跟踪。该系统实时工作,捕获和显示之间的时间间隔最短。此外,整个系统在速度,内存要求以及所使用的逻辑元件数量方面都进行了优化,使其适合于实时监控系统。

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