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Real-time locating system for high speed and dim target based on FPGA

机译:基于FPGA的高速微弱目标实时定位系统

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In test-range tracking, traditional machine vision systems are composed of a frame grabber and a host PC, which cannot meet the requirement of real-time processing. In this paper, we present a real-time locating system based on FPGA (Field Programmable Gate Array) to solve problems caused by high-speed and low-sharpness of the target in field testing. FPGA, as the system processing core, captures the high resolution images from TDI-CCD (Time delay and integration charge coupled device) line scan camera which is based on Camera Link interface. Two SRAM chips are used in this system to store line images alternately. The high frame frequency image data are stored in one SRAM chip by stitching and finishing while the data from the other are processed to analyze the target. Adaptive threshold and smooth filtering methods are proposed to get rid of the environmental or false target interference. For identifying the dim target from the mass sequential images, energy accumulation and frame difference are presented to reduce the false target alarm rate. Also, the sub-pixel grayscale centroid algorithm is presented in this paper to improve the location accuracy. Experimental results demonstrate that the pipelined architecture system can fulfill data acquisition and processing on frame frequency of 15000 frame/s with the line scan images of 8192 × 1 pixels in real time.
机译:在测试范围跟踪中,传统的机器视觉系统由抓帧器和主机PC组成,无法满足实时处理的要求。在本文中,我们提出了一种基于FPGA(现场可编程门阵列)的实时定位系统,以解决目标测试中目标物的高速和低清晰度问题。 FPGA作为系统处理核心,从基于Camera Link接口的TDI-CCD(时延和积分电荷耦合器件)线扫描相机捕获高分辨率图像。该系统中使用了两个SRAM芯片来交替存储线图像。高帧频图像数据通过缝合和精加工存储在一个SRAM芯片中,同时处理来自另一帧的数据以分析目标。提出了自适应阈值和平滑滤波方法,以消除环境或虚假目标干扰。为了从整体序列图像中识别昏暗目标,提出了能量积累和帧差以减少虚假目标报警率。此外,本文提出了亚像素灰度质心算法,以提高定位精度。实验结果表明,流水线架构系统可以实时地以8192×1像素的线扫描图像完成15000帧/秒的帧频数据采集和处理。

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