A dynamic threshold system with DFT compound motion analysis

This paper is concerned with investigating, experiencing, and validating a local adaptive threshold system with compound motion analysis. The motivation here is to analyze moving objects in outdoor/indoor video frames with respect to: movement detection, objects segmentation, features extraction besides DFT-based velocity computation. The underlying methodology exhibits a single correlation of the behavioral-mathematical model of the examined image sequences among 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 inspection, 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, surveillance, and general civil and military fields.