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Staelens, S., and I. Lemahieu, "Monte Carlo Based Image Reconstruction in Emission Tom ography", Computational Intelligence in Medical Imaging: Techniques and Applications: CRC Press, pp. 407, 2009. Abstract
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Staelens, S., and I. Lemahieu, "Monte Carlo Based Image Reconstruction in Emission Tom ography", Computational Intelligence in Medical Imaging: Techniques and Applications: CRC Press, pp. 407, 2009. Abstract
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Soliman, O. S., Jan Platoš, A. E. Hassanien, and Václav Snášel, "Automatic localization and boundary detection of retina in images using basic image processing filters", Proceedings of the Third International Conference on Intelligent Human Computer Interaction (IHCI 2011), Prague, Czech Republic, August, 2011: Springer Berlin Heidelberg, pp. 169–182, 2013. Abstract
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Soliman, M. M., A. E. Hassanien, and H. M. Onsi, "A Blind 3D Watermarking Approach for 3D Mesh Using Clustering Based Methods", International Journal of Computer Vision and Image Processing (IJCVIP), vol. 3, no. 2: IGI Global, pp. 43–53, 2013. Abstract
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Soliman, M. M., A. E. Hassanien, and H. M. Onsi, "An adaptive watermarking approach based on weighted quantum particle swarm optimization", Neural Computing and Applications, vol. 27, no. 2: Springer London, pp. 469–481, 2016. Abstract
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Soliman, O. S., Jan Platoš, A. E. Hassanien, and Václav Snášel, "Automatic localization and boundary detection of retina in images using basic image processing filters", Proceedings of the Third International Conference on Intelligent Human Computer Interaction (IHCI 2011), Prague, Czech Republic, August, 2011: Springer Berlin Heidelberg, pp. 169–182, 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", Intelligent Systems' 2014: Springer International Publishing, pp. 731–741, 2015. Abstract
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Soliman, H., M. A. Fattah, and A. E. Hassanien, "Cloud Computing Framework for Solving Virtiual College Educations", The Second International Conference on INformation systems Design and Intelligent Applications ((INDIA 15), Kalyani, India, January 8-9 , 2015.
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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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., and A. E. Hassanien, "3D Watermarking Approach Using Particle Swarm Optimization Algorithm", Handbook of Research on Machine Learning Innovations and Trends, USA, IGI, 2017. Abstract

This work proposes a watermarking approach by utilizing the use of Bio-Inspired techniques such as swarm intelligent in optimizing watermarking algorithms for 3D models. In this proposed work we present an approach of 3D mesh model watermarking by introducing a new robust 3D mesh watermarking authentication methods by ensuring a minimal surface distortion at the same time ensuring a high robustness of extracted watermark. In order to achieve these requirements this work proposes the use of Particle Swarm Optimization (PSO) as Bio-Inspired optimization techniques. The experiments were executed using different sets of 3D models. In all experimental results we consider two important factors: imperceptibility and robustness. The experimental results show that the proposed approach yields a watermarked object with good visual definition; at the same time, the embedded watermark was robust against a wide variety of common attacks.

Soliman, M. M., A. E. Hassanien, and H. M. Onsi, "The way of improving PSO performance: medical imaging watermarking case study", International Conference on Rough Sets and Current Trends in Computing: Springer Berlin Heidelberg, pp. 237–242, 2012. Abstract
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Soliman, M. M., A. E. Hassanien, N. I. Ghali, and H. M. Onsi, "An adaptive watermarking approach for medical imaging using swarm intelligent", International Journal of Smart Home, vol. 6, no. 1, pp. 37–50, 2012. Abstract
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Soliman, O. S., and A. E. Hassanien, "A Computer Aided Diagnosis System for Breast Cancer Using Support Vector Machine", International Conference on Rough Sets and Current Trends in Computing: Springer Berlin Heidelberg, pp. 106–115, 2012. Abstract
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Soliman, M. M., A. E. Hassanien, and H. M. Onsi, "A Blind 3D Watermarking Approach for 3D Mesh Using Clustering Based Methods", International Journal of Computer Vision and Image Processing (IJCVIP), vol. 3, no. 2: IGI Global, pp. 43–53, 2013. Abstract
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Soliman, O. S., and A. E. Hassanien, "A Computer Aided Diagnosis System for Breast Cancer Using Support Vector Machine", International Conference on Rough Sets and Current Trends in Computing: Springer Berlin Heidelberg, pp. 106–115, 2012. Abstract
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Soliman, M. M., A. E. Hassanien, and H. M. Onsi, "A Blind Robust 3D-Watermarking Scheme Based on Progressive Mesh and Self Organization Maps", Advances in Security of Information and Communication Networks: Springer Berlin Heidelberg, pp. 131–142, 2013. Abstract
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Soliman, M. M., A. E. Hassanien, N. I. Ghali, and H. M. Onsi, "An adaptive Watermarking Approach for Medical Imaging Using Swarm Intelligent", International Journal of Smart Home, (ISSN: 1975-4094), vol. 6, issue 1, pp. 37-45, 2012. AbstractIJSH_ 2012.pdfWebsite

In this paper we present a secure patient medical images and authentication scheme which enhances the security, confidentiality and integrity of medical images transmitted through the Internet. This paper proposes a watermarking by invoking particle swarm optimization (PSO) technique in adaptive quantization index modulation and singular value decomposition in conjunction with discrete wavelet transform (DWT) and discrete cosine transform (DCT). The proposed approach promotes the robustness and watermarked image quality. The experimental results show that the proposed algorithm yields a watermark which is invisible to human eyes, robust against a wide variety of common attacks and reliable enough for tracing colluders.

Soliman, M. M., A. E. Hassanien, and H. M. Onsi, "An adaptive watermarking approach based on weighted quantum particle swarm optimization", Neural Computing and Applications, vol. 27, issue 2, pp. 469–481, 2016. AbstractWebsite

In this paper, we propose a novel optimal singular value decomposition (SVD)-based image watermarking approach that uses a new combination of weighted quantum particle swarm optimization (WQPSO) algorithm and a human visual system (HVS) model for both the hybrid discrete wavelet transform and discrete cosine transform (DCT). The proposed SVD-based watermarking approach initially decomposes the host image into sub-bands; afterwards, singular values of the DCT of the lower sub-band of the host image are quantized using a set of optimal quantization steps deduced from a combination of the WQPSO algorithm and the HVS model. To evaluate the performance of the proposed approach, we present tests on different images. The experimental results show that the proposed approach yields a watermarked image with good visual definition; at the same time, the embedded watermark was robust against a wide variety of common attacks, including JPEG compression, Gaussian noise, salt and pepper noises, Gaussian filters, median filters, image cropping, and image scaling. Moreover, the results of various experimental analyses demonstrated the superiority of the WQPSO approach over other optimization techniques, including classical PSO and QPSO in terms of local convergence speed, resulting in a better balance between global and local searches of the watermarking algorithm.

Soliman, M. M., and A. E. Hassanien, "3D Watermarking Approach Using Particle Swarm Optimization Algorithm", Handbook of Research on Machine Learning Innovations and Trends: IGI Global, pp. 582–613, 2017. Abstract
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Soliman, O. S., A. E. Hassanien, N. I. Ghali, N. El-Bendary, and R. A. Sarker, "A model-based decision support tool using fuzzy optimization for climate change", International Conference on Rough Sets and Knowledge Technology: Springer Berlin Heidelberg, pp. 388–393, 2011. Abstract
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Soliman, M. M., A. E. Hassanien, and H. M. Onsi, "An adaptive medical images watermarking using quantum particle swarm optimization", Telecommunications and Signal Processing (TSP), 2012 35th International Conference on: IEEE, pp. 735–739, 2012. Abstract
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Soliman, O. S., A. E. Hassanien, N. I. Ghali, N. El-Bendary, and R. A. Sarker, "A model-based decision support tool using fuzzy optimization for climate change", International Conference on Rough Sets and Knowledge Technology: Springer Berlin Heidelberg, pp. 388–393, 2011. Abstract
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Soliman, O. S., Jan Platoš, A. E. Hassanien, and Václav Snášel, "Automatic localization and boundary detection of retina in images using basic image processing filters", Proceedings of the Third International Conference on Intelligent Human Computer Interaction (IHCI 2011), Prague, Czech Republic, August, 2011: Springer Berlin Heidelberg, pp. 169–182, 2013. Abstract
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Soliman, M. M., A. E. Hassanien, N. I. Ghali, and H. M. Onsi, "An adaptive watermarking approach for medical imaging using swarm intelligent", International Journal of Smart Home, vol. 6, no. 1, pp. 37–50, 2012. Abstract
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