Papers by Fathi Abdul-samee3
Menoufia Journal of Electronic Engineering Research
Climate change is destroying many crops around the world. This paper aims to anticipate maize yie... more Climate change is destroying many crops around the world. This paper aims to anticipate maize yield levels based on climatic conditions, which would aid in making proper decisions regarding the connected sectors for business planning and yield level prediction. This paper presents two novel models that combine five machine learning algorithms with different techniques. Selecting six months of the climate features for the four regions in China. The first proposed model (FPM) consists of K Nearest Neighbors, Multinomial Naïve Bayes, Bernoulli Naïve Bayes, Decision Tree and Quadratic Discriminant Analysis (KMBDQ) that come together in a cascading topology (CT) to feed each other by taking the new prediction and removing the old previous prediction from the input features at each stage. The second proposed model (SPM) also uses the same five machine learning algorithms with different approaches. In this model, the prediction of each machine learning algorithm is used as a feeder to each other in the form of CT without removing any prediction. The performance evaluation of the proposed models was demonstrated and compared with several classifiers using the same dataset. The evaluation was based on metrics such as accuracy, sensitivity, precision, and F1 score. The results showed that the SPM had the highest prediction accuracy of 79.6%, which was a 29.6% increase compared to the first classifier in the model. The SPM also had an 11.1% improvement compared to the FPM and a 10.2% increase compared to the best among the many techniques used. In addition, computation time comparisons were conducted.
Journal of Ambient Intelligence and Humanized Computing
Convolutional Neural Networks (CNNs) are efficient tools for pattern recognition applications. Th... more Convolutional Neural Networks (CNNs) are efficient tools for pattern recognition applications. They have found applications in wireless communication systems such as modulation classification from constellation diagrams. Unfortunately, noisy channels may render the constellation points deformed and scattered, which makes the classification a difficult task. This paper presents an efficient modulation classification algorithm based on CNNs. Constellation diagrams are generated for each modulation type and used for training and testing of the CNNs. The proposed work depends on the application of Radon Transform (RT) to generate more representative patterns for the constellation diagrams to be used for training and testing. The RT has a good ability to represent discrete points in the spatial domain as curved lines. Several pre-trained networks including AlexNet, VGG-16, and VGG-19 are used as classifiers for modulation type from the spatial-domain constellation diagrams or their RTs. ...
Efficient communication and EEG signal classification in wavelet domain for epilepsy patients
Journal of Ambient Intelligence and Humanized Computing
In this paper, we present an approach for the anticipation of electroencephalography (EEG) seizur... more In this paper, we present an approach for the anticipation of electroencephalography (EEG) seizures using different families of wavelet transform. Different signal attributes are investigated to anticipate the seizure onset based on the wavelet transform. These attributes comprise amplitude, local mean, local median, local variance, derivative, and entropy of the wavelet-transformed signals. Different wavelet families are considered including Haar, Daubechies (db4, and db8), Symlets (Sym4), and Coiflets (Coif4) wavelets. The seizure prediction process is intended to be simple to be applied on a mobile application accompanying the patient to give him alerts of possible incoming seizures. The proposed approach is performed on long-term EEG recordings from the available CHB-MIT scalp dataset. It gives the best results in comparison with the other previous algorithms. It achieves a high sensitivity of 100% with Daubechies wavelet transform (db4) in addition to a low average False Prediction Rate (FPR) of 0.0818 h−1 and a high average Prediction Time (PT) of 38.1676 min. Therefore, it can help specialists for the prediction of epileptic seizures as early as possible.
Secure audio signal transmission based on color image watermarking
SECURITY AND PRIVACY, 2021
This paper presents a new color image watermarking system with encrypted audio signals using sing... more This paper presents a new color image watermarking system with encrypted audio signals using singular value decomposition (SVD), Arnold, and chaotic techniques for secure audio transmission over open channels. This system is based on embedding encrypted audio watermarks after transforming them into a 2‐D format in the singular values of the color cover image components. Three different audio watermarks are embedded in the three color image components after separating the cover image into its red, green and blue components. The three resulting watermarked components are merged again to produce the final color watermarked image. To maintain the audio signal quality, we estimate some audio signal quality metrics after converting the audio signal into a 1‐D format. The transformation from the 1‐D to 2‐D formats is performed through lexicographic ordering. Simulation results demonstrate that the proposed system preserves the high quality of the RGB cover image. In addition, the audio wat...
IEEE Access, 2021
A hybrid multistates orbital angular momentum-multi pulse-position modulation (N OAM-MPPM) scheme... more A hybrid multistates orbital angular momentum-multi pulse-position modulation (N OAM-MPPM) scheme over gamma-gamma free-space optical (ΓΓ-FSO) channel is studied in this paper. In our study, all atmospheric and pointing error impacts are taken into account. Expressions for the parameters of ΓΓ-FSO-pointing error channel are derived. In addition, approximate-tight upper bounds on the biterror rates (BERs) of N OAM and N OAM-MPPM techniques are developed over ΓΓ-FSO-pointing error channels, considering the influences of beam divergence and pointing error. The ΓΓ-FSO-PE channel parameters and the BER expressions are evaluated numerically and verified by simulation. It turned out that the analytical results are nearly the same to that obtained from simulation under diverse turbulence scenarios and OAM modes. The results demonstrate that under variable turbulence conditions, the N OAM-MPPM technique outperforms both ordinary N OAM and MPPM systems. Furthermore, different deep learning (DL) techniques, namely random forest (RF), convolution neural network (CNN), and auto-encoder (AE), are employed to get optimum classification accuracy using different datasets of N OAM-MPPM-ΓΓ-PE model. Finally, the results indicate that AE has the best performance metrics of DL compared to other models using different datasets. INDEX TERMS free-space optic (FSO), multiple pulse-position modulation (MPPM), orbital angular momentum (OAM), pointing error.
Menoufia Journal of Electronic Engineering Research, 2021
This paper introduces three cancelable speaker identification techniques based on the spectrogram... more This paper introduces three cancelable speaker identification techniques based on the spectrogram estimation of speech signals subjected to either chaotic encryption process, or RSA algorithm in addition to Radon transform to produce cancelable templates instead of the original speech signals. The resulting transformed versions of the voice biometrics are stored in the server instead of the original biometrics. Therefore, the users' privacy can be protected well. It is evident from the obtained results that the proposed techniques are secure, reliable and practical. They have good encryption and ability to generate cancelable templates. These characteristics lead to good performance. The proposed cancelable speaker identification techniques are evaluated under the influence of Additive White Gaussian Noise (AWGN) with different strengths. This makes them more accurate in identifying the users and also more resistant to attack attempts. In addition, security is enhanced through maintaining the confidentiality of the processed data. In the experimental results, evaluation metrics such as Equal Error Rate (EER), False Rejection Rate (FRR), and False Acceptance Rate (FAR) are used to assess the performance of the proposed techniques. In addition, the genuine, impostor distributions, Receiver Operating Characteristic (ROC) curve and area under the ROC curve for the proposed techniques are estimated for better evaluation and comparison.
Multimedia Tools and Applications, 2020
Segmentation and classification of ultrasonic breast images is extremely critical for medical dia... more Segmentation and classification of ultrasonic breast images is extremely critical for medical diagnosis. Over the last years, various techniques have already been presented for this objective. In this paper, a proposed framework is presented to segment a given ultrasonic image with breast tumor and classify the tumor as being benign or malignant. The proposed framework depends on an active contour segmentation model to determine the tumor region, and then extract it from the ultrasonic image. After that, the Discrete Wavelet Transform (DWT) is used to extract features from the segmented images. Then, the dimensions of the resulting features are reduced by applying feature reduction approaches, namely, the Principal Component Analysis (PCA), the Linear Discriminant Analysis (LDA) and both of them together. The obtained features are submitted to a statistical classifier and the strategy of voting is used to classify the tumor. In the simulation work, 160 benign and malignant breast tumor images collected from Sirindhorn International Institute of Technology (SIIT) website are used. The average processing time for a 256 × 256 image on a laptop with Core i5, 2.3 GHz processor and 8GB RAM is 1.8 s. From the simulation results, it is found that the utilization of the PCA approach provides the best accuracy of 99.23% among the three feature reduction approaches applied. Finally, the proposed framework is compared with the Support Vector Machine (SVM) classification to evaluate its performance in terms of accuracy, sensitivity, precision, and specificity. It is noticed that the proposed framework is efficient and rapid, and it can be applied for ultrasonic breast image segmentation and classification, and thus it can assist the specialists to segment and decide whether a tumor is benign or malignant.
Multimedia Tools and Applications, 2020
This research presents new three proposed approaches to enhancement the visibility of the Infrare... more This research presents new three proposed approaches to enhancement the visibility of the Infrared (IR) night vision images. The first proposed approach depends on Hybrid Adaptive Gamma Correction (AGC) with Histogram Matching (HGCHM). The second proposed approach stands up Merging Gamma Correction with Contrast Limited Adaptive Histogram Equalization (MGCCLAHE). The HM uses a reference visual image for converting of night vision images into daytime images. The third approach mixes the benefits of the CLAHE with the undecimated Additive Wavelet Transform (AWT) Using Homomorphic processing (CSAWUH). The quality assessments for the suggested approaches are entropy, average gradient, contrast improvement factor, Sobel edge magnitude, spectral entropy, lightness order error and the similarity of edges. Simulation results clear that the third proposed approach gives superior results to the two proposed approaches from entropy, average gradient, contrast improvement factor, Sobel edge magnitude, spectral entropy and the computation time perspectives. On the other hand, the second proposed approach takes long computation time in the implementation with respect to the two proposed approaches. The second proposed approach gives better results to the first proposed approach entropy, average gradient, contrast improvement factor, Sobel edge magnitude, and spectral entropy perspectives. The first proposed approach gives better results to the two proposed approaches from lightness order error and the similarity of edges perspectives.
Smart Health Monitoring System based on IoT and Cloud Computing
Menoufia Journal of Electronic Engineering Research, 2019
This paper presents a secure IoT-based health monitoring system that shortens the distance betwee... more This paper presents a secure IoT-based health monitoring system that shortens the distance between a patient and the relevant medical organization. Vital signals captured from sensors are processed and encrypted using AES (Advanced Encryption Standard) algorithm before sending to the cloud for storage. A Node MCU microcontroller is utilized to carry out the processing and encryption functions, and for providing connectivity to the cloud over WiFi. In addition, a medical specialist can visualize the private health data in real-time only after providing decryption credentials. Moreover, the proposed system provides an alert by sending an email to some patient relatives or coordinating specialist if vital signs are outside the normal rates. The proposed system provides privacy, security, and real-time connectivity for private health data records.
Menoufia Journal of Electronic Engineering Research, 2020
This paper presents a computer-based framework for the segmentation of medical eye images. Also, ... more This paper presents a computer-based framework for the segmentation of medical eye images. Also, the proposed framework achieves the detection of exudates in medical eye images for better diagnosis of maculopathy disease. The proposed framework begins with fuzzy image enhancement of eye images for contrast enhancement in order to enhance the objects representation of the images. After that, the segmentation process is performed to determine the optic disc and blood vessels to remove them. The next step is detecting the region of interest edges in exudates. A gradient process is also performed on the image and the histogram of gradient is evaluated. Accumulative histogram is further generated for discrimination between image with and without exudates. A threshold histogram curve is generated based on predefined images with and without exudates for classification of images in the testing phase. The simulation results prove that the proposed framework has an appreciated performance.
Menoufia Journal of Electronic Engineering Research, 2020
Pan-sharpening considers one of the most important applications for satellite images as it enhanc... more Pan-sharpening considers one of the most important applications for satellite images as it enhances spectral and spatial information for the images. Empirical Mode Decomposition (EMD) is one of the most powerful techniques for pan-sharpening. It first decomposes the image into a set of Intrinsic Mode Functions (IMFs) and a residual component. These panchromatic and multispectral components are then fused to create an enhanced pan-sharpened image. This paper presents an efficient hybrid method for enhancing pansharpening of multiband images transmitted from satellite to ground stations. The proposed approach combines this EMD technique with the most powerful conventional method; Discrete Wavelet Transform (DWT), to maximize the pan-sharpening gain. The proposed hybrid method is validated using satellite images of Nile Valley and Suez Canal region, Egypt, captured by Spot-4 and Landsat-8 satellites. The results imply that the proposed hybrid method provides better qualitative and quantitative quality comparing with the individual and the most common pan-sharpening methods.
Menoufia Journal of Electronic Engineering Research, 2020
Reverberation is one of the effects that occur regularly in closed room due to multiple reflectio... more Reverberation is one of the effects that occur regularly in closed room due to multiple reflections. This paper investigates the result of reverberation on both male and female speech signals. This effect is reflected in pitch frequency of speech signals. This parameter is important as it is usually used for speaker identification. Hence, several methods for pitch frequency estimation are investigated and compared on clear and reverberant male and female speech signals to select the one that is not affected so much by the reverberation effect.
Multimedia Tools and Applications, 2019
This paper presents a proposed approach for the enhancement of Infrared (IR) night vision images.... more This paper presents a proposed approach for the enhancement of Infrared (IR) night vision images. This approach is based on a trilateral contrast enhancement in which the IR night vision images pass through three stages: segmentation, enhancement and sharpening. In the first stage, the IR image is divided into segments based on thresholding. The second stage, which is the heart of the enhancement approach, depends on additive wavelet transform (AWT) to decompose the image into an approximation and details. Homomorphic enhancement is performed on the detail components, while plateau histogram equalization is performed on the approximation plane. Then, the image is reconstructed and subjected to a postprocessing high-pass filter. Average gradient, Sobel edge magnitude and spectral entropy are used as quality metrics for evaluation of the proposed approach. The used metrics ensure good success of this proposed approach.
Efficient anomaly detection from medical signals and images
International Journal of Speech Technology, 2019
Anomaly detection is a very vital area in medical signal and image processing due to its importan... more Anomaly detection is a very vital area in medical signal and image processing due to its importance in automatic diagnosis. This paper presents three efficient anomaly detection approaches for applications related to Electroencephalogram (EEG) signal processing and retinal image processing. The first approach depends on the utilization of Scale-Invariant Feature Transform (SIFT) for automatic seizure detection. The second one is based on the utilization of digital filters in a statistical framework for seizure prediction. Finally, an automated Diabetic Retinopathy (DR) diagnosis approach is presented based on the segmentation and detection of anomalous objects from retinal images. The presented simulation results reveal the success of the proposed techniques towards automated medical diagnosis.
Multimedia Tools and Applications, 2019
This paper presents two proposed approaches for enhancing the visibility of the infrared (IR) nig... more This paper presents two proposed approaches for enhancing the visibility of the infrared (IR) night vision images. The first approach is based on merging gamma correction with histogram matching (HM). On the other hand, the second approach depends on merging gamma correction with contrast limited adaptive histogram equalization (CLAHE). The HM depends on a reference visual image for converting IR night vision images into images with better visual quality. Quality metrics such as entropy, average gradient, and Sobel edge magnitude are used for performance evaluation of the proposed approaches.
Bluetooth performance improvement over different channels through channel coding
2008 5th International Multi-Conference on Systems, Signals and Devices, 2008
An Integrated Image Fusion Technique for Boosting the Quality of Noisy Remote Sensing Images
2007 National Radio Science Conference, 2007
To better identify the objects in remote sensing images, the muItispectral images with high spect... more To better identify the objects in remote sensing images, the muItispectral images with high spectral resolution and low spatial resolution, and the panchromatic images with high spatial resolution and low spectral resolution need to be fused. Many fusion techniques are discussed in the recent years to obtain images with high spectral resolution and also high spatial resolution. In this paper
Simultaneous blind signal separation and denoising
2008 International Conference on Computer Engineering & Systems, 2008
Chaotic Interleaving for Robust Image Transmission with LDPC Coded OFDM
Wireless Personal Communications, 2014
An efficient fusion technique for quality enhancement of remotely sensed images
Applied Geomatics, 2014
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Papers by Fathi Abdul-samee3