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Schaefer, G., Qinghua Hu, H. Zhou, J. F. Peters, and A. E. Hassanien, "Rough c-means and fuzzy rough c-means for colour quantisation", Fundamenta Informaticae, vol. 119, no. 1: IOS Press, pp. 113–120, 2012. Abstract
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Soliman, M. M., A. E. Hassanien, and H. M. Onsi, "Robust watermarking approach for 3D triangular mesh using self organization map", Computer Engineering & Systems (ICCES), 2013 8th International Conference on: IEEE, pp. 99–104, 2013. Abstract
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Awad, A. I., H. M. Zawbaa, H. A. Mahmoud, E. H. H. A. Nabi, R. H. Fayed, and A. E. Hassanien, "A robust cattle identification scheme using muzzle print images", Computer Science and Information Systems (FedCSIS), 2013 Federated Conference on: IEEE, pp. 529–534, 2013. Abstract
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Awad, A. I., H. M. Zawbaa, H. A. Mahmoud, E. H. H. A. Nabi, R. H. Fayed, and A. E. Hassanien, "A robust cattle identification scheme using muzzle print images", Computer Science and Information Systems (FedCSIS), 2013 Federated Conference on: IEEE, pp. 529–534, 2013. Abstract
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Soliman, M. M., A. E. Hassanien, and H. M. Onsi, "A Robust 3D Mesh Watermarking Approach Using Genetic Algorithms", IEEE Intelligent Systems'2014, Poland - Warsaw , 24 -26 Sept. , 2014. Abstract

This paper proposes a new approach of 3D watermarking by ensuring the optimal preservation of mesh surfaces. The minimal surface distortion is enforced during watermark embedding stage using Genetic Algorithm (GA) optimization. The watermark embedding is performed only on set of selected vertices come out from k-means clustering technique. These vertices are used as candidates for watermark carriers that will hold watermark bits stream. A 3D surface preservation function is defined according to the distance of a vertex displaced by watermarking to the original surface. A study of the proposed methodology has high robustness against the common mesh attacks while preserving the original object surface during watermarking.

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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Adham Mohamed, H. M. Zawbaa, M. M. M. Fouad, Esraa Elhariri, N. El-Bendary, Mohamed Tahoun, and A. E. Hassanine, "RoadMonitor: An Intelligent Road Surface Condition Monitoring System", IEEE Conf. on Intelligent Systems (2) 2014: 377-387, Poland - Warsaw , 24 -26 Sept. , 2014. Abstract

Well maintained road network is an essential requirement for the safety and consistency of vehicles moving on that road and the wellbeing of people in those vehicles. On the other hand, guaranteeing an adequate maintenance by road managers can be achieved via having sufficient and accurate information concerning road infrastructure quality that can be as well utilized concurrently by the widespread means of users’ mobile devices both locally and worldwide. This article proposes a road condition monitoring framework that detects the road anomalies such as speed bumps. In the proposed approach, the main indicator for road anomalies is the gyroscope around gravity rotation in addition to the accelerometer sensor as a cross-validation method to confirm the detection results that were gathered from the gyroscope.

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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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.

Asad, A. H., Eid Elamry, and A. E. Hassanien, "Retinal vessels segmentation based on water flooding model", The 9th IEEE International Computer Engineering Conference (ICENCO 2013) pp. 43 - 48 , Cairo, EGYPT -, December 29-30, , 2013.
Asad, A. H., Eid Elamry, and A. E. Hassanien, "Retinal vessels segmentation based on water flooding model", Computer Engineering Conference (ICENCO), 2013 9th International: IEEE, pp. 43–48, 2013. Abstract
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Eid Emary, H. M. Zawbaa, A. E. Hassanien, G. Schaefer, and A. T. Azar, "Retinal vessel segmentation based on possibilistic fuzzy c-means clustering optimised with cuckoo search", Neural Networks (IJCNN), 2014 International Joint Conference on: IEEE, pp. 1792–1796, 2014. Abstract
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E. Emary, H. M. Zawbaa, boul Ella Hassanien, M. F. Tolba, and V. Snasel, ""Retinal vessel segmentation based on flower pollination search algorithm"", The 5th International Conference on Innovations in Bio-Inspired Computing and Applications (Springer), Ostrava, Czech Republic., 23-24 June, 2014. Abstractibica2014_p11.pdf

This paper presents an automated retinal blood vessels segmentation
approach based on flower pollination search algorithm (FPSA). The flower pollination
search is a new algorithm based on the flower pollination process of flowering
plants. The FPSA searches for the optimal clustering of the given retinal
image into compact clusters under some constrains. Shape features are used to
further enhance the clustering results using local search method. The proposed
retinal blood vessels approach is tested on a publicly available databases DRIVE
a of retinal images. The results demonstrate that the performance of the proposed
approach is comparable with state of the art techniques in terms of accuracy, sensitivity
and specificity.

Eid Emary, H. M. Zawbaa, A. E. Hassanien, M. F. Tolba, and Václav Snášel, "Retinal vessel segmentation based on flower pollination search algorithm", Proceedings of the Fifth International Conference on Innovations in Bio-Inspired Computing and Applications IBICA 2014: Springer International Publishing, pp. 93–100, 2014. Abstract
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Hassan, G., and A. E. Hassanien, "Retinal fundus vasculature multilevel segmentation using whale optimization algorithm", Signal, Image and Video Processing, vol. 12, issue 2, pp. 263–270, 2018. AbstractWebsite

The aim was to present a novel automated approach for extracting the vasculature of retinal fundus images. The proposed vasculature extraction method on retinal fundus images consists of two phases: preprocessing phase and segmentation phase. In the first phase, brightness enhancement is applied for the retinal fundus images. For the vessel segmentation phase, a hybrid model of multilevel thresholding along with whale optimization algorithm (WOA) is performed. WOA is used to improve the segmentation accuracy through finding the n−1 optimal n-level threshold on the fundus image. To evaluate the accuracy, sensitivity, specificity, accuracy, receiver operating characteristic (ROC) curve analysis measurements are used. The proposed approach achieved an overall accuracy of 97.8%, sensitivity of 88.9%, and specificity of 98.7% for the identification of retinal blood vessels by using a dataset that was collected from Bostan diagnostic center in Fayoum city. The area under the ROC curve reached a value of 0.967. Automated identification of retinal blood vessels based on whale algorithm seems highly successful through a comprehensive optimization process of operational parameters.

Heba, T., E. - B. Nashwa, H. AboulElla, B. Yehia, and S. Vaclav, "Retinal Feature-Based Registration Schema", Informatics Engineering and Information Science Communications in Computer and Information Science Volume 252, 2011, pp 26-36 , Ostrava, Czech Republic, 7-9 July, 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.

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.

Taha, H. M., N. El-Bendary, A. E. Hassanien, Y. Badr, and V. Snasel, "Retinal feature-based registration schema", Informatics engineering and information science: Springer Berlin Heidelberg, pp. 26–36, 2011. Abstract
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Taha, H. M., N. El-Bendary, A. E. Hassanien, Y. Badr, and V. Snasel, "Retinal feature-based registration schema", Informatics engineering and information science: Springer Berlin Heidelberg, pp. 26–36, 2011. Abstract
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Eid Emary, H. M. Zawbaa, A. E. Hassanien, G. Schaefer, and A. T. Azar, "Retinal blood vessel segmentation using bee colony optimisation and pattern search", Neural Networks (IJCNN), 2014 International Joint Conference on: IEEE, pp. 1001–1006, 2014. Abstract
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Hassan, G., N. El-Bendary, A. E. Hassanien, S. A. M. Ali Fahmy, and V. Snasel, "Retinal Blood Vessel Segmentation Approach Based on Mathematical Morphology", International Conference on Communications, management, and Information technology (ICCMIT'2015), 2015. Abstract

Diabetic retinopathy is a disease, which forms a severe threat on sight. It may reach to blindness among working age people. By analyzing and detecting of vasculature structures in retinal images, we can early detect the diabetes in advanced stages by comparison of its states of retinal blood vessels. In this paper, we present blood vessel segmentation approach, which can be used in computer based retinal image analysis to extract the retinal image vessels. Mathematical morphology and K-means clustering are used to segment the vessels. To enhance the blood vessels and suppress the background information, we perform smoothing operation on the retinal image using mathematical morphology. Then the enhanced image is segmented using K-means clustering algorithm. The proposed approach is tested on the DRIVE dataset and is compared with alternative approaches. Experimental results obtained by the proposed approach showed that it is effective as it achieved average accuracy of 95.10% and best accuracy of 96.25%.

Hassan, G., N. El-Bendary, A. E. Hassanien, A. Fahmy, V. Snasel, and others, "Retinal blood vessel segmentation approach based on mathematical morphology", Procedia Computer Science, vol. 65: Elsevier, pp. 612–622, 2015. Abstract
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Hassaniena, A. E., E. Emarya, and H. M. Zawbaa, "Retinal blood vessel localization approach based on bee colony swarm optimization, fuzzy c-means and pattern search.", J. Visual Communication and Image Representation , vol. 31, pp. 186-196 , 2015. AbstractWebsite

Accurate segmentation of retinal blood vessels is an important task in computer aided diagnosis and surgery planning of retinopathy. Despite the high resolution of photographs in fundus photography, the contrast between the blood vessels and retinal background tends to be poor. Furthermore, pathological changes of the retinal vessel tree can be observed in a variety of diseases such as diabetes and glaucoma. Vessels with small diameters are much liable to effects of diseases and imaging problems. In this paper, an automated retinal blood vessels segmentation approach based on two levels optimization principles is proposed. The proposed approach makes use of the artificial bee colony optimization in conjunction with fuzzy cluster compactness fitness function with partial belongness in the first level to find coarse vessels. The dependency on the vessel reflectance is problematic as the confusion with background and vessel distortions especially for thin vessels, so we made use of a second level of optimization. In the second level of optimization, pattern search is further used to enhance the segmentation results using shape description as a complementary feature. Thinness ratio is used as a fitness function for the pattern search optimization. The pattern search is a powerful tool for local search while artificial bee colony is a global search with high convergence speed. The proposed retinal blood vessels segmentation approach is tested on two publicly available databases DRIVE and STARE of retinal images. The results demonstrate that the performance of the proposed approach is comparable with state of the art techniques in terms of sensitivity, specificity and accuracy.

Hassanien, A. E., Eid Emary, and H. M. Zawbaa, "Retinal blood vessel localization approach based on bee colony swarm optimization, fuzzy c-means and pattern search", Journal of Visual Communication and Image Representation, vol. 31: Academic Press, pp. 186–196, 2015. Abstract
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Gaber, T., A. E. Hassanien, and M. F. Tolba, "Repeated reselling permission multi-reselling approach for a license in DRM environment", Hybrid Intelligent Systems (HIS), 2013 13th International Conference on: IEEE, pp. 197–202, 2013. Abstract
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Tourism