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Modified dynamic threshold system with DFT multifarious motion analysis

机译:具有DFT多种运动分析功能的改进型动态阈值系统

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This paper is concerned with investigating, experiencing, and validating a dynamic threshold system with multifarious motion analysis. The motivation here is to introduce a method for analyzing moving objects in outdoor/indoor video frames with respect to: movement detection, objects segmentation, features extraction besides DFT-based velocity computation. The underlying methodology believes in cross-fertilizing the two independent segmentation approaches of back-ground subtraction and temporal frames differencing through a single correlation exhibiting the behavioral-mathematical model of the examined image sequences. This has been interpreted through identifying the image as time-varying functions applicable for processing through 2D Discrete Fourier Transform (DFT). The justification of this method has been revealed through output data, human visual perceptual inspection, plus histogramming; showing appreciable accuracy, lower level of noise, and shorter segmentation time in comparison with some availa-ble standard techniques. The horizon of applications of the presented method may involve: security control, industry and traffic control, athletic and dancing performance evaluation, surveillance, and general civil and military fields.
机译:本文涉及通过多种运动分析研究,体验和验证动态阈值系统。此处的动机是引入一种方法,除了基于DFT的速度计算之外,还可以分析以下内容:运动检测,对象分割,特征提取,室外/室内视频帧中的运动对象。基本的方法论认为,通过展示所检查图像序列的行为数学模型的单个相关性,可以相互融合背景减法和时间帧差异这两种独立的分割方法。通过将图像识别为适用于2D离散傅里叶变换(DFT)进行处理的时变函数,可以对此进行解释。通过输出数据,人类视觉感知检查以及直方图揭示了这种方法的合理性。与某些可用的标准技术相比,它显示出可观的准确性,较低的噪声水平和较短的分割时间。所提出的方法的应用范围可能涉及:安全控制,工业和交通控制,运动和舞蹈表演评估,监视以及一般的民用和军事领域。

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