M.Abd Elnaby

Work place: Faculty of Engineering, Tanta University, Egypt

E-mail: mnaby45@gmail.com


Research Interests: Medical Image Computing, Image Processing, Image Manipulation, Image Compression, Operating Systems, Computer Architecture and Organization, Pattern Recognition, Computer Vision, Computer systems and computational processes


Mustafa Abdelnabi is a Professor of Electronics and Electrical Communication Engineering, Faculty of Engineering, Tanta University, Algarbia, Egypt. Field of specialization: Image processing, Medical imaging, Machine learning, Biomedical. Systems, Pattern recognition, Signal/image/video processing, Image analysis, Computer vision, Mathematical Modeling and Computer Simulation, Modeling of Biomedical Systems, Robotics and Systems, Computer Aided Diagnosis and Optimization. Total number of publications in Scopus about 88 publications

Author Articles
Traffic Video Enhancement based Vehicle Correct Tracked Methodology

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

DOI: https://doi.org/10.5815/ijigsp.2017.12.04, 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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