Publications

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Book Chapter
Ghali, N. I., W. G. Abd-Elmonim, and A. E. Hassanien, Object-Based Image Retrieval System Using Rough Set Approach, , London, Advances in Reasoning-Based Image Processing Intelligent Systems Intelligent Systems Reference Library, 2012, Volume 29, Part 2, 315-329, 2012. Abstract

In this chapter, we present an object-based image retrieval system using the rough set theory. The system incorporates two major modules: Pre-processing and Object-based image retrieval. In pre processing, an image based object segmentation algorithm in the context of the rough set theory is used to segment the images into meaningful semantic regions. A new object similarity measure is proposed for the image retrieval. Performance is evaluated on an image database and the effectiveness of proposed image retrieval system is demonstrated. Experimental results show that the proposed system performs well in terms of speed and accuracy.

Ghali, N. I., W. G. Abd-Elmonim, and A. E. Hassanien, "Object-based image retrieval system using rough set approach", Advances in Reasoning-Based Image Processing Intelligent Systems: Springer Berlin Heidelberg, pp. 315–329, 2012. Abstract
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Ghali, N. I., W. G. Abd-Elmonim, and A. E. Hassanien, "Object-based image retrieval system using rough set approach", Advances in Reasoning-Based Image Processing Intelligent Systems: Springer Berlin Heidelberg, pp. 315–329, 2012. Abstract
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Soliman, M. M., A. E. Hassanien, and H. M. Onsi, "An Optimized Approach for Medical Image Watermarking", Bio-inspiring Cyber Security and Cloud Services: Trends and Innovations: Springer Berlin Heidelberg, pp. 71–91, 2014. Abstract
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Abdelaziz, A., Moustafa Zein, M. Atef, A. Adl, K. K. A. Ghany, and A. E. Hassanien, "An Orphan Drug Legislation System", Intelligent Systems' 2014: Springer International Publishing, pp. 389–399, 2015. Abstract
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Gaber, T., and A. E. Hassanien, "An Overview of Self-Protection and Self-Healing in Wireless Sensor Networks", Bio-inspiring Cyber Security and Cloud Services: Trends and Innovations: Springer Berlin Heidelberg, pp. 185–202, 2014. Abstract
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Abder-Rahman Ali, Micael Couceiro, A. Anter, and A. - E. Hassanien, "Particle swarm optimization based fast fuzzy C-means clustering for liver CT segmentation", Applications of Intelligent Optimization in Biology and Medicine: Springer International Publishing, pp. 233–250, 2016. Abstract
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Tharwt, A., and A. E. Hassanien, "Particle Swarm Optimization: A Tutorial", Handbook of Research on Machine Learning Innovations and Trends, USA, IGI, 2017. Abstract

Optimization algorithms are necessary to solve many problems such as parameter tuning. Particle Swarm Optimization (PSO) is one of these optimization algorithms. The aim of PSO is to search for the optimal solution in the search space. This paper highlights the basic background needed to understand and implement the PSO algorithm. This paper starts with basic definitions of the PSO algorithm and how the particles are moved in the search space to find the optimal or near optimal solution. Moreover, a numerical example is illustrated to show how the particles are moved in a convex optimization problem. Another numerical example is illustrated to show how the PSO trapped in a local minima problem. Two experiments are conducted to show how the PSO searches for the optimal parameters in one-dimensional and two-dimensional spaces to solve machine learning problems.

Alaa Tharwat, T. Gaber, A. E. Hassanien, and B. E. Elnaghi, "Particle Swarm Optimization: A Tutorial", Handbook of Research on Machine Learning Innovations and Trends: IGI Global, pp. 614–635, 2017. Abstract
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Yakoub, F., Moustafa Zein, K. Yasser, A. Adl, and A. E. Hassanien, "Predicting personality traits and social context based on mining the smartphones SMS data", Intelligent Data Analysis and Applications: Springer International Publishing, pp. 511–521, 2015. Abstract
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Fattah, M. A., N. El-Bendary, M. A. A. Elsoud, Jan Platoš, and A. E. Hassanien, "Principal component analysis neural network hybrid Classification Approach for Galaxies Images", Innovations in Bio-inspired Computing and Applications: Springer International Publishing, pp. 225–237, 2014. Abstract
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Farouk, A., M. Elhoseny, and A. E. Hassanien, "A Proposed Architecture for Key Management Schema in Centralized Quantum Network", Handbook of Research on Machine Learning Innovations and Trends, USA, IGI, 2017. Abstract

Most existing realizations of quantum key distribution (QKD) are point-to-point systems with one source transferring to only one destination. Growth of these single-receiver systems has now achieved a reasonably sophisticated point. However, many communication systems operate in a point-to-multi-point (Multicast) configuration rather than in point-to-point mode, so it is crucial to demonstrate compatibility with this type of network in order to maximize the application range for QKD. Therefore, this chapter proposed architecture for implementing a multicast quantum key distribution Schema. The proposed architecture is designed as a Multicast Centralized Key Management Scheme Using Quantum Key Distribution and Classical Symmetric Encryption. In this architecture, a secured key generation and distribution solution has been proposed for a single host sending to two or more (N) receivers using centralized Quantum Multicast Key Distribution Centre and classical symmetric encryption.

Farouk, A., M. Elhoseny, J. Batle, M. Naseri, and A. E. Hassanien, "A Proposed Architecture for Key Management Schema in Centralized Quantum Network", Handbook of Research on Machine Learning Innovations and Trends: IGI Global, pp. 997–1021, 2017. Abstract
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Hassanien, A. E., G. Schaefer, and H. AlQaheri, "Prostate Boundary Detection in Ultrasound Images Based on Type-II Fuzzy Sets and Modified Fuzzy C-Means", Soft Computing in Industrial Applications: Springer Berlin Heidelberg, pp. 187–195, 2010. Abstract
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Hassanien, A. E., G. Schaefer, and H. AlQaheri, "Prostate Boundary Detection in Ultrasound Images Based on Type-II Fuzzy Sets and Modified Fuzzy C-Means", Soft Computing in Industrial Applications: Springer Berlin Heidelberg, pp. 187–195, 2010. Abstract
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Hore, S., T. Bhattacharya, N. Dey, A. E. Hassanien, A. Banerjee, and S. R. B. Chaudhuri, "A Real Time Dactylology Based Feature Extractrion for Selective Image Encryption and Artificial Neural Network", Image Feature Detectors and Descriptors: Springer International Publishing, pp. 203–226, 2016. Abstract
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Reham Gharbia, Ali Hassan El Baz, A. E. Hassanien, and V. Snasel, "Region-based Image Fusion Approach of Panchromatic and Multi-spectral Images", Intelligent Data Analysis and Applications: Springer International Publishing, pp. 535–545, 2015. Abstract
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Mohamed Tahoun, A. E. Hassanien, and R. Reulke, "Registration of Optical and Radar Satellite Images Using Local Features and Non-rigid Geometric Transformations", Surface Models for Geosciences: Springer International Publishing, pp. 249–261, 2015. Abstract
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Sahba, F., H. R. Tizhoosh, and M. M. A. Salama, "Reinforced Medical Image Segmentation", Computational Intelligence in Medical Imaging: Techniques and Applications: Chapman and Hall/CRC, pp. 327–345, 2009. Abstract
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Reham Gharbia, S. A. Ahmed, and A. E. Hassanien, "Remote Sensing Image Registration Based on Particle Swarm Optimization and Mutual Information", Information Systems Design and Intelligent Applications: Springer India, pp. 399–408, 2015. Abstract
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Heba M. Taha, N. El-Bendary, A. E. Hassanien, Y. Badr, and V. Snasel, "Retinal Feature-Based Registration Schema", Informatics Engineering and Information Science, Berlin Heidelberg, pp. 26-36, Communications in Computer and Information Science - Springer , 2011. Abstract

This paper presents a feature-based retinal image registration schema. A structural feature, namely, bifurcation structure, has been used for the proposed feature-based registration schema. The bifurcation structure is composed of a master bifurcation point and its three connected neighbors. The characteristic vector of each bifurcation structure consists of the normalized branching angle and length, which is invariant against translation, rotation, scaling, and even modest distortion. The proposed schema is composed of five fundamental phases, namely, input retinal images pre-processing, vascular network detection, noise removal, bifurcation points detection in vascular networks, and bifurcation points matching in pairs of retinal images. The effectiveness of the proposed schema is demonstrated by the experiments with 12 pairs retinal images collected from clinical patients. The registration is carried out through optimizing a certain similarity function, namely, normalized correlation of images. It has been observed that the proposed schema has achieved good performance accuracy.

Hassan, G., and A. E. Hassanien, "A Review of Vessel Segmentation Methodologies and Algorithms: Comprehensive Review, ", Handbook of Research on Machine Learning Innovations and Trends, USA, IGI USA, 2017. Abstract

“Prevention is better than cure”, true statement which all of us neglect. One of the most reasons which cause speedy recovery from any diseases is to discover it in advanced stages. From here come the importance of computer systems which preserve time and achieve accurate results in knowing the diseases and its first symptoms .One of these systems is retinal image analysis system which considered as a key role and the first step of Computer Aided Diagnosis Systems (CAD). In addition to monitor the patient health status under different treatment methods to ensure How it effects on the disease.. In this chapter the authors examine most of approaches that are used for vessel segmentation for retinal images, and a review of techniques is presented comparing between their quality and accessibility, analyzing and catgrizing them. This chapter gives a description and highlights the key points and the performance measures of each one.

Adham Mohamed, M. M. M. Fouad, Esraa Elhariri, N. El-Bendary, H. M. Zawbaa, Mohamed Tahoun, and A. E. Hassanien, "RoadMonitor: an intelligent road surface condition monitoring system", Intelligent Systems' 2014: Springer International Publishing, pp. 377–387, 2015. Abstract
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Soliman, M. M., A. E. Hassanien, and H. M. Onsi, "A Robust 3D Mesh Watermarking Approach Using Genetic Algorithms", Intelligent Systems' 2014: Springer International Publishing, pp. 731–741, 2015. Abstract
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Hassanien, A. E., H. Al-Qaheri, and A. Abraham, "Rough Hybrid Scheme", Rough Fuzzy Image Analysis: Foundations and Methodologies: CRC Press, pp. 5–1, 2010. Abstract
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