0000000000327700
AUTHOR
Mohamad Mazen Hittawe
showing 3 related works from this author
Electrocardiogram Signal Analysing
2016
In this paper, we develop a new approach based on nonlinear filtering scheme (NLFS) on cardiac signal to evaluate a robust single-lead electrocardiogram (ECG) delineation system and waves localization method based on nonlinear filtering approach. This system is built in two phases, in the first phase, we proposed a mathematical model for detecting ECG features like QRS complex peak, P and T-waves onsets and ends fromnoise free of synthetic ECG signal. Later, we develop a theoretical model to obtain real approach for detecting these features from real noisy ECG signals. Our method has been evaluated on electrocardiogram signals of QT-MIT standard database, the QRS peak achieve sensitivity (S…
Fast Earth Mover's Distance Computation for Catadioptric Image Sequences
2016
International audience; Earth mover's distance is one of the most effective metric for comparing histograms in various image retrieval applications. The main drawback is its computational complexity which hinders its usage in various comparison tasks. We propose fast earth mover's distance computation by providing better initialization to the transportation simplex algorithm. The new approach enables faster EMD computation in Visual Memory (VM) compared to the state of the art methods. The new proposed strategy computes earth mover distance without compromising its accuracy.
Bag of words representation and SVM classifier for timber knots detection on color images
2015
Knots as well as their density have a huge impact on the mechanical properties of wood boards. This paper addresses the issue of their automatic detection. An image processing pipeline which associates low level processing (contrast enhancement, thresholding, mathematical morphology) with bag-of-words approach is developed. We propose a SVM classification based on features obtained by SURF descriptors on RGB images, followed by a dictionary created using the bag-of-words approach. Our method was tested on color images from two different datasets with a total number of 640 knots. The mean recall (true positive) rate achieved was (92%) and (97%) for a single dictionary (built only on samples …