Mohamed El-Darieby

Work place: Faculty of Engineering, University of Regina, Canada.



Research Interests: Data Structures and Algorithms, Computing Platform, Computer Networks, Computer Architecture and Organization


Mohamed El-Darieby (M’98) is an associate professor of Software Systems Engineering at the Faculty of Engineering at the University of Regina, Regina, Canada. He received B.Sc. and electrical engineering from Egypt and Ph.D in Systems and Computer Engineering at Carleton University, Ottawa, Canada. His research is in the areas of backbone networks, grid computing and wireless mesh networks. Dr. El-Darieby is a member of the IEEE and the Association of Professional Engineers and Geoscientists of Saskatchewan (APEGS).

Author Articles
Traffic Video Enhancement based Vehicle Correct Tracked Methodology

By Mohamed Maher Ata Mohamed El-Darieby M.Abd Elnaby Sameh A. Napoleon

DOI:, Pub. Date: 8 Dec. 2017

In this paper, an enhancement based traffic video has been proposed in the state of the art of computer vision. The main target is to develop a decision making criteria for removing the most probable video degradations. Such traffic video degradations would have an adverse impact on the transportation system. In order to establish the appropriate analysis, three types of video degradations have been added to the test video; salt and pepper noise, Gaussian noise, and speckle noise, we have simulated rainy, fog, and darkness conditions for the traffic video. First of all, back ground subtraction and Kalman filter techniques have been used for detecting and tracking vehicles respectively. By using such algorithms, it would be easily to estimate average number of assigned tracks which express the efficacy of correct detection and prediction of vehicles in each frame.  Furthermore, video degradations would be applied in order to studying its effect on the average number of assigned tracks which would be deviated than noiseless video. Spatial filtering system has been applied to state the most suitable filter mask which satisfy the least deviation in the average number of assigned tracks. Experimental results show that median filter satisfies the least deviation in all cases of video degradations.

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