Papers by Mohamed Roushdy
In this paper, classified and comparative study of edge detection algorithms are presented. Exper... more In this paper, classified and comparative study of edge detection algorithms are presented. Experimental results prove that Boie-Cox, Shen-Castan and Canny operators are better than Laplacian of Gaussian (LOG), while LOG is better than Prewitt and Sobel in case of noisy image. Subjective and objective methods are used to evaluate the different edge operators. The morphological filter is more important as an initial process in the edge detection for noisy image and used opening-closing operation as preprocessing to filter noise. Also, smooth the image by first closing and then dilation to enhance the image before the edge operators affect.
One of the key problems of restoring a degraded image from motion blur is the estimation of the u... more One of the key problems of restoring a degraded image from motion blur is the estimation of the unknown non-linear blur filter from a single input blurred image. Many blind deconvolution methods typically assume frequency-domain constraints on images, simplified parametric forms for the motion path during camera shake or use multiple input images with specific characteristics. This paper proposes an algorithm for removing nonlinear motion blur from a single input blurred image using Genetic Algorithms (GAs), by finding the proper parameters and goal function. Also recent research in natural image statistics is exploited, which shows that photographs of natural scenes typically obey heavy-tailed distribution. The Point Spread Function entries are used as the parameters of the GA. Experiments on a wide data set of standard images degraded with different kernels of different sizes demonstrate the efficiency of the proposed approach especially in small blur lengths compared to other algorithms with reasonable running times for a GA.
In this paper, we have used the Case Based Reasoning methodology to develop a case-based expert s... more In this paper, we have used the Case Based Reasoning methodology to develop a case-based expert system prototype for supporting diagnosis of heart diseases. 110 cases were collected for 4 heart diseases namely; mitral stenosis, left-sided heart failure, stable angina pectoris and essential hypertension. Each case contains 207 attributes concerning both demographic and clinical data. After removing the duplicated cases, the system has trained set of 42 cases for Egyptian cardiac patients. Statistical analysis has been done to determine the importance values of the case features. Two retrieval strategies were investigated namely; induction and nearest-neighbor approaches. The results indicate that the nearest neighbor is better than the induction strategy, where the retrieval accuracy were 100% and 53.8% respectively. Cardiologists have evaluated the overall system performance where the system was able to give a correct diagnosis for thirteen new cases.
Egyptian Computer Science Journal, 2001
Hough transform is a general technique for identifying the locations and orientations of certain ... more Hough transform is a general technique for identifying the locations and orientations of certain types of features in a digital image and used to isolate features of a particular shape within an image. Because it requires that the desired features are specified in some parametric form, classical Hough transform is the most commonly used for the detection of regular curves
The 7th International Conference on Information Technology, 2015
Medical Ontologies play a central role in integrating heterogeneous databases of various model or... more Medical Ontologies play a central role in integrating heterogeneous databases of various model organisms. Hepatobiliary system is very important to human vital processes. It has an ability to regulate the other systems. Furthermore, it may be affected by many pathologic conditions, which affect other organs negatively. This paper investigates the current studies on Ontological engineering approach and Ontology techniques for Hepatobiliary System Diseases. We present conceptual view for the Hepatobiliary system and its infected diseases. Besides, we propose a new classification schema for the research efforts investigated so far. We classified the research efforts investigated so far based on the Hepatobiliary system organs: Liver, Gallbladder, Bile duct and Pancreas. Besides, we discuss the current research gaps found in this research area.
Neuromuscular disorders affect the nerves that control arms and legs muscles specially stroke. St... more Neuromuscular disorders affect the nerves that control arms and legs muscles specially stroke. Stroke may cause problems with thinking, awareness, attention, learning, judgment, and memory and can lead to emotional problems. Stroke patients may have difficulty controlling their emotions or may express inappropriate emotions. Electromyography (EMG) signal provide a significant source of information for identification of neuromuscular disorders. This paper investigates the usage of support vector machine (SVM) classifiers with different kernel functions for identification of different hands and legs, normal and auto aggressive actions from EMG data. We made a comparison between classifications accuracies of each kernel function applied on different groups of actions.
Users are always looking for the next method for securing computer based systems because unauthor... more Users are always looking for the next method for securing computer based systems because unauthorized users are always trying to find means of accessing the secured systems. With the advances in computer hardware it’s getting easier for unauthorized users to develop techniques that try to pass the existing security measures. Electroencephalogram (EEG) is the recording of electrical activity from the surface of the brain. It is proved that there is a significant amount of individuality in the EEG signals, accordingly its can be used as a biometric for user identification. In this paper, we present an artificial immune system inspired approach for identifying users using EEG signals. The Physionet EEG Motor/Movement/ Imagery dataset is used to validate this approach. The dataset consists of signals for over a hundred users. The dataset is imported to EEG lab for the preprocessing phase, then we use artificial immune system based algorithm for user matching.
Mapping and localization of robots in an unknown environment is a complicated but essential task ... more Mapping and localization of robots in an unknown environment is a complicated but essential task for navigation and further operations. This has made researchers eager to solve this problem and accordingly many techniques have been investigated using different types of sensors. In this paper we address the Simultaneous Localization and Mapping (SLAM) problem using colored and depth images. We present an overview of the most known techniques with focus on the graph-based mapping, along with a comparison of different algorithms used in registration and optimization. The system is tested on a standard 3D datasets of indoor environment.
This paper applies the knowledge discovery process over medical data set using the rough set theo... more This paper applies the knowledge discovery process over medical data set using the rough set theory as a data mining technique. The aim is to apply rough set concepts and the reduction algorithm to search for patterns specific/sensitive to thrombosis disease. The mining efforts show that the developed reduction algorithm minimizes the set of original attributes from 60 to 16
Egyptian Computer Science Journal, 2002
Egyptian Computer Science Journal, 2001
One of the key problems of restoring a degraded image from motion blur is the estimation of the u... more One of the key problems of restoring a degraded image from motion blur is the estimation of the unknown nonlinear blur filter from a single input blurred image. Many blind deconvolution methods typically assume frequency-domain constraints on images, simplified parametric forms for the motion path during camera shake or use multiple input images with specific characteristics. The paper proposes an
SEG Technical Program Expanded Abstracts 2003, 2003
ABSTRACT In this paper, classified and comparative study of edge detection algorithms are present... more ABSTRACT In this paper, classified and comparative study of edge detection algorithms are presented. Experimental results prove that Boie-Cox, Shen-Castan and Canny operators are better than Laplacian of Gaussian (LOG), while LOG is better than Prewitt and Sobel in case of noisy image. Subjective and objective methods are used to evaluate the different edge operators. The morphological filter is more important as an initial process in the edge detection for noisy image and used opening-closing operation as preprocessing to filter noise. Also, smooth the image by first closing and then dilation to enhance the image before the edge operators affect.
International Journal of Advanced Computer Science and Applications, 2010
Most digital image forgery detection techniques require the doubtful image to be uncompressed and... more Most digital image forgery detection techniques require the doubtful image to be uncompressed and in high quality. However, most image acquisition and editing tools use the JPEG standard for image compression. The histogram of Discrete Cosine Transform coefficients contains information on the compression parameters for JPEGs and previously compressed bitmaps. In this paper we present a straightforward method to estimate the quantization table from the peaks of the histogram of DCT coefficients. The estimated table is then used with two distortion measures to deem images as untouched or forged. Testing the procedure on a large set of images gave a reasonable average estimation accuracy of 80% that increases up to 88% with increasing quality factors. Forgery detection tests on four different types of tampering resulted in an average false negative rate of 7.95% and 4.35% for the two measures respectively.
Egyptian Computer Science Journal - ECS, 2004
Proceedings of the international …, 2003
In this paper, we have used the Case Based Reasoning methodology to develop a case-based expert s... more In this paper, we have used the Case Based Reasoning methodology to develop a case-based expert system prototype for supporting diagnosis of heart diseases. 110 cases were collected for 4 heart diseases namely; mitral stenosis, left-sided heart failure, stable ...
Electroencephalography (EEG) is the recording of electrical activity occurring in the brain, whic... more Electroencephalography (EEG) is the recording of electrical activity occurring in the brain, which is recorded from the scalp through placement of voltage sensitive electrodes. It has been repeatedly demonstrated that the brain emits voltage fluctuations on a continuous basis. These fluctuations are a reflection of the on-going brain dynamics, which present as a series of fluctuations that have characteristic waveforms and amplitude patterns, depending on the cognitive state of the
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Papers by Mohamed Roushdy