Analysis of dynamic images in machine vision and its application study in motion control

Dong Xia, Wang Ke-dian
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引用次数: 4

Abstract

Recent advances in high performance computing coupled with the decreasing cost of hardware now make machine vision a financially viable inspection option for even small and medium sized firms. Amongst many problems relative to the machine vision applications, the detection and tracking of moving targets is very important in many cases including industrial fields. Our challenge is to develop an effective methodology on analysis of dynamic images able to extract the moving target by using only visual sensing as input and keeping computation time and hardware cost to a minimum, typically with a standard Pentium-based computer and a standard CCD camera. This paper presents a segmentation method combining dynamic segmentation with static segmentation and examines moving object detection based primarily on inter-frame difference method. We applied the methods into the motion control of a familiar work table driving system only based on machine vision. The experimental results demonstrate that in realistic situations, detection of moving targets by using inter-frame difference method is more effective than that by using optical flow method.
机器视觉中的动态图像分析及其在运动控制中的应用研究
高性能计算的最新进展,加上硬件成本的下降,现在使机器视觉成为一种经济上可行的检测选择,即使是中小型公司。在许多与机器视觉应用相关的问题中,运动目标的检测和跟踪在包括工业领域在内的许多情况下都是非常重要的。我们面临的挑战是开发一种有效的动态图像分析方法,能够通过仅使用视觉传感作为输入来提取运动目标,并将计算时间和硬件成本降至最低,通常使用标准的基于奔腾的计算机和标准CCD相机。本文提出了一种动态分割与静态分割相结合的分割方法,主要研究了基于帧间差分法的运动目标检测。我们将这些方法应用到一个简单的基于机器视觉的工作台驱动系统的运动控制中。实验结果表明,在实际情况下,采用帧间差分法检测运动目标比采用光流法检测运动目标更有效。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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