Modified dynamic threshold system with DFT multifarious motion analysis

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 available 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.