Publications

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Book Chapter
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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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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Mohamed Tahoun, Abd El Rahman Shabayek, H. Nassar, M. M. Giovenco, R. Reulke, Eid Emary, and A. E. Hassanien, "Satellite Image Matching and Registration: A Comparative Study Using Invariant Local Features", Image Feature Detectors and Descriptors: Springer International Publishing, pp. 135–171, 2016. Abstract
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El-Bendary, N., Mohamed Mostafa M. Fouad, Rabie A. Ramadan, S. Banerjee, and A. E. Hassanien, "Smart Environmental Monitoring Using Wireless Sensor Networks.", Wireless Sensor Networks: Theory and Applications, pp. 733-755, , USA, CRC Press, Taylor and Francis Group, 2013. k15146_c025.pdf
Conference Paper
El-Atta, A. A. H., M. I. Moussa, and A. E. Hassenian, " Predicting biological activity of 2,4,6-trisubstituted 1,3,5-triazines", 5ththe 5th International Conference on Innovations in Bio-Inspired Computing and Applications - IBICA2014 (Springer), Ostrava, Czech Republic., 22-24 June, 2013.
Moftah, H. M., A. E. Hassanien, A. M. Alimi, H. Karray, and M. F. Tolba, "Ant-based clustering algorithm for magnetic resonance breast image segmentation", Hybrid Intelligent Systems (HIS), 2013 13th International Conference on: IEEE, pp. 161–166, 2013. Abstract
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Mostafa, A., M. Houseni, N. Allam, A. E. Hassanien, H. Hefny, and P. - W. Tsai, "Antlion Optimization Based Segmentation for MRI Liver Images", International Conference on Genetic and Evolutionary Computing: Springer International Publishing, pp. 265–272, 2016. Abstract
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Fattah, M. A., A. E. Hassanien, A. Mostafa, A. F. Ali, K. M. Amin, and S. MOHAMED, "Artificial bee colony optimizer for historical Arabic manuscript images binarization", Computer Engineering Conference (ICENCO), 2015 11th International: IEEE, pp. 251–255, 2015. Abstract
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Mahir M. Sharif, Alaa Tharwat, A. E. H. H. H. A., "Automated Enzyme Function Classification Based on Pairwise Sequence Alignment Technique", Proceedings of the Second Euro-China Conference on Intelligent Data Analysis and Applications (Springer), ECC 2015, , Ostrava, Czech Republic, June 29 - July 1, 2015. Abstract

Enzymes are important in our life due to its importance in the most biological processes. Thus, classification of the enzyme’s function is vital to save efforts and time in the labs. In this paper, we propose an approach based on sequence alignment to compute the similarity between any two sequences. In the proposed approach, two different sequence alignment methods are used, namely, local and global sequence alignment. There are different score matrices such as BLOSUM and PAM are used in the local and global alignment to calculate the similarity between the unknown sequence and each sequence of the training sequences. The results which obtained were acceptable to some extent compared to previous studies that have surveyed.

Elhoseny, M., N. Metawa, and A. E. Hassanien, "An automated information system to ensure quality in higher education institutions", 2016 12th International Computer Engineering Conference (ICENCO), , Cairo, 28-29 Dec. 2016. Abstract

Despite the great efforts to assure quality in higher education institutions, the ambiguity of its related concepts and requirements constitute a big challenge when trying to implement it as an automated information system. The present work introduces a framework for an automated information system that manages the quality assurance in higher educations institutions. The aim of designing such a system is to provide an automation tool that avoids unnecessary and redundant tasks associated to quality in higher education institutions. In addition, the proposed system helps all higher education stockholders to handle and monitor their tasks. Moreover, it aims to help the quality assurance center in a higher education institution to apply its qualitys standards, and to make sure that they are being maintained and enhanced. This information system contains a core module and 17 sub-modules, which are described in this paper.

Elhoseny, M., N. Metawa, and A. E. Hassanien, "An automated information system to ensure quality in higher education institutions", Computer Engineering Conference (ICENCO), 2016 12th International: IEEE, pp. 196–201, 2016. Abstract
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Elhoseny, M., N. Metawa, and A. E. Hassanien, "An automated information system to ensure quality in higher education institutions,", 2016 12th International Computer Engineering Conference (ICENCO), , Cairo, 28-29 Dec, 2016. Abstract

Despite the great efforts to assure quality in higher education institutions, the ambiguity of its related concepts and requirements constitute a big challenge when trying to implement it as an automated information system. The present work introduces a framework for an automated information system that manages the quality assurance in higher educations institutions. The aim of designing such a system is to provide an automation tool that avoids unnecessary and redundant tasks associated to quality in higher education institutions. In addition, the proposed system helps all higher education stockholders to handle and monitor their tasks. Moreover, it aims to help the quality assurance center in a higher education institution to apply its qualitys standards, and to make sure that they are being maintained and enhanced. This information system contains a core module and 17 sub-modules, which are described in this paper.

Mouhamed, M. R., A. M. Rashad, and A. E. Hassanien, "Blind 2D vector data watermarking approach using random table and polar coordinates", Uncertainty Reasoning and Knowledge Engineering (URKE), 2012 2nd International Conference on: IEEE, pp. 67–70, 2012. Abstract
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Mouhamed, M. R., H. M. Zawbaa, E. Al-Shammari, A. E. Hassanien, and V. Snasel, "Blind Watermark Approach for Map Authentication using Support Vector Machine", International conference on Advances in Security of Information and Communication Networks, (SecNet 2013) , Springer pp. 84–97, Cairo - Egypt, 3-5 Sept, 2013, . blind_watermark_approach_for_map_authentication_svm.pdf
Mahmoud, H. A., H. M. El Hadad, F. A. Mousa, and A. E. Hassanien, "Cattle classifications system using Fuzzy K-Nearest Neighbor Classifier", Informatics, Electronics & Vision (ICIEV), 2015 International Conference on: IEEE, pp. 1–5, 2015. Abstract
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Mahmood, M. A., N. El-Bendary, A. E. Hassanien, and H. A. Hefny, "Classification Approach based on Rough Mereology", In Proceedings of the Second International Symposium on Intelligent Informatics (ISI'13), , Mysore, India, 23-24 August, 20, 2013. isi2013-india-classification_approach_based_on_rough_mereology.pdf
Abdelsalam, M., Mahmood A. Mahmood, Yasser Mahmoud Awad, M. Hazman, N. Elbendary, A. E. Hassanien, M. F. Tolba, and S. M. Saleh, "Climate recommender system for wheat cultivation in North Egyptian Sinai Peninsula", The 5th International Conference on Innovations in Bio-Inspired Computing and Applications (Springer) IBICA2014, Ostrava, Czech Republic., 22-24 June, 2013.
Abdelsalam, M., M. A. Mahmood, Yasser Mahmoud Awad, M. Hazman, N. Elbendary, A. E. Hassanien, M. F. Tolba, and S. M. Saleh, "Climate recommender system for wheat cultivation in North Egyptian Sinai Peninsula", Proceedings of the Fifth International Conference on Innovations in Bio-Inspired Computing and Applications IBICA 2014: Springer International Publishing, pp. 121–130, 2014. Abstract
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Mohamed Tahoun, Abd El Rahman Shabayek, R. Reulke, and A. E. Hassanien, "Co-registration of Satellite Images Based on Invariant Local Features", IEEE Conf. on Intelligent Systems (2) 2014: 653-660, Poland - Warsaw , 24 -26 Sept. , 2014. Abstract

Detection and matching of features from satellite images taken from different sensors, viewpoints, or at different times are important tasks when manipulating and processing remote sensing data for many applications. This paper presents a scheme for satellite image co-registration using invariant local features. Different corner and scale based feature detectors have been tested during the keypoint extraction, descriptor construction and matching processes. The framework suggests a sub-sampling process which controls the number of extracted key points for a real time processing and for minimizing the hardware requirements. After getting the pairwise matches between the input images, a full registration process is followed by applying bundle adjustment and image warping then compositing the registered version. Harris and GFTT have recorded good results with ASTER images while both with SURF give the most stable performance on optical images in terms of better inliers ratios and running time compared to the other detectors. SIFT detector has recorded the best inliers ratios on TerraSAR-X data while it still has a weak performance with other optical images like Rapid-Eye and ASTER.

Mostafa, A., M. A. Fattah, A. E. Hassanien, H. Hefny, and G. S. Shao Ying Zhu, "CT Liver Segmentation Using Artificial Bee Colony Optimisation", 19th International Conference on Knowledge Based and Intelligent Information and Engineering Systems, Procedia Computer Science , Singapore, September, 2015. Abstract

The automated segmentation of the liver area is an essential phase in liver diagnosis from medical images. In this paper, we propose an artificial bee colony (ABC) optimisation algorithm that is used as a clustering technique to segment the liver in CT images. In our algorithm, ABC calculates the centroids of clusters in the image together with the region corresponding to each cluster. Using mathematical morphological operations, we then remove small and thin regions, which may represents flesh regions around the liver area, sharp edges of organs or small lesions inside the liver. The extracted regions are integrated to give an initial estimate of the liver area. In a final step, this is further enhanced using a region growing approach. In our experiments, we employed a set of 38 images, taken in pre-contrast phase, and the similarity index calculated to judge the performance of our proposed approach. This experimental evaluation confirmed our approach to afford a very good segmentation accuracy of 93.73% on the test dataset.

Mostafa, A., M. A. Fattah, A. Ali, and A. E. Hassanin, "Enhanced Region Growing Segmentation For CT Liver Images", the 1st International Conference on Advanced Intelligent Systems and Informatics (AISI’15) Springer, . Beni Suef University, Beni Suef, Egypt , Nov. 28-30 , 2015. Abstract

This paper intends to enhance the image for the next usage
of region growing technique for segmenting the region of liver away from
other organs. The approach depends on a preprocessing phase to enhance
the appearance of the boundaries of the liver. This is performed using
contrast stretching and some morphological operations to prepare the
image for next segmentation phase. The approach starts with combining
Otsu's global thresholding with dilation and erosion to remove image
annotation and machine's bed. The second step of image preparation
is to connect ribs, and apply lters to enhance image and deepen liver
boundaries. The combined lters are contrast stretching and texture l-
ters. The last step is to use a simple region growing technique, which has
low computational cost, but ignored for its low accuracy. The proposed
approach is appropriate for many images, where liver could not be sep-
arated before, because of the similarity of the intensity with other close
organs. A set of 44 images taken in pre-contrast phase, were used to test
the approach. Validating the approach has been done using similarity
index. The experimental results, show that the overall accuracy o ered
by the proposed approach results in 91.3% accuracy.

Mostafa, A., M. A. Fattah, A. Fouad, A. E. Hassanien, and H. Hefny, "Enhanced region growing segmentation for CT liver images", The 1st International Conference on Advanced Intelligent System and Informatics (AISI2015), November 28-30, 2015, Beni Suef, Egypt: Springer International Publishing, pp. 115–127, 2016. Abstract
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Mostafa, A., H. Hefny, N. I. Ghali, A. E. Hassanien, and G. Schaefer, "Evaluating the effects of image filters in CT liver CAD system", Biomedical and Health Informatics (BHI), 2012 IEEE-EMBS International Conference on: IEEE, pp. 448–451, 2012. Abstract
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Mostafa, A., H. Hefny, N. I. Ghali, A. E. Hassanien, and G. Schaefer, "Evaluating the effects of image filters in CT liver CAD system", Biomedical and Health Informatics (BHI), 2012 IEEE-EMBS International Conference on: IEEE, pp. 448–451, 2012. Abstract
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Mostafa, A., H. Hefny, N. I. Ghali, A. E. Hassanien, and G. Schaefer, "Evaluating the effects of image filters in CT liver CAD system", Biomedical and Health Informatics (BHI), 2012 IEEE-EMBS International Conference on: IEEE, pp. 448–451, 2012. Abstract
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