Publications

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Miscellaneous
Li, T., H. S. Nguyen, G. Wang, J. W. Grzymala-Busse, R. Janicki, A. - E. Hassanien, and H. Yu, Rough Sets and Knowledge Technology: 7th International Conference, RSKT 2012, Chengdu, China, August 17-20, 2012, Proceedings, : Springer, 2012. Abstract
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Li, T., H. S. Nguyen, G. Wang, J. W. Grzymala-Busse, R. Janicki, A. - E. Hassanien, and H. Yu, Rough Sets and Knowledge Technology: 7th International Conference, RSKT 2012, Chengdu, China, August 17-20, 2012, Proceedings, : Springer, 2012. Abstract
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Journal Article
Lamiaa M. El Bakrawy, N. I.Ghali, T. - H. Kim, and A. E. Hassanien, "A Block-wise-based Fragile Watermarking Hybrid Approach using Rough Sets and Exponential Particle Swarm Optimization ", Journal of Future Generation Communication and Networking, , vol. 4, issue 4, 2011. Abstractblock-wise-based_fragile_watermarking.pdf

In this paper, we propose a fragile watermarking hybrid approach using rough set kmeans and exponential particle swarm optimization (EPSO) systems. It is based on a block-wise dependency mechanism which can detect any alterations made to the protected image. Initially, the input image is divided into blocks with equal size in order to improve image tamper localization precision. Then feature sequence is generated by applying rough k-means and EPSO clustering to create the relationship between all image blocks and cluster
all of them since EPSO is used to optimize the parameters of rough k-means. Both feature sequence and generated secret key are used to construct the authentication data. Each resultant 8-bit authentication data is embedded into the eight least significant bits (LSBs) of the corresponding image block. We gives experimental results which show the feasibility of using these optimization algorithms for the fragile watermarking and demonstrate the
accuracy of the proposed approach. The performance comparison of the approach was also realized. The performance of a fragile watermarking approach has been improved in this paper by using exponential particle swarm optimization (EPSO) to optimize the rough kmean parameters. The proposed approach can embed watermark without causing noticeable visual artifacts, and does not only achieve superior tamper detection in images accurately,
it also recovers tampered regions effectively. In addition, the results show that the proposed approach can effectively thwart different attacks, such as the cut-and paste attack and collage attack, while sustaining superior tamper detection and localization accuracy.

Xiao, K., L. A. Liang, Haibing Guan, and A. E. Hassanien, "Extraction and application of deformation-based feature in medical images", Neurocomputing, vol. 120: Elsevier, pp. 177–184, 2013. Abstract
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Xiao, K., L. A. Liang, Haibing Guan, and A. E. Hassanien, "Extraction and application of deformation-based feature in medical images", Neurocomputing, vol. 120: Elsevier, pp. 177–184, 2013. Abstract
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Xia, K., J. Li, H. G. Shuangjiu Xiao, F. Fang, and A. E. Hassanien, "Fuzzy Clustering with Multi-resolution Bilateral Filtering for Medical Image Segmentation", International Journal of Fuzzy System Applications (IJFSA), vol. 3, issue 4, 2013. fuzzy_clustering_with_multi-resolution_bilateral_filtering_for_medical_image_segmentation-revision.pdf
Xiao, K., J. Li, S. Xiao, Haibing Guan, F. Fang, and A. E. Hassanien, "Fuzzy Clustering with Multi-Resolution Bilateral Filtering for Medical Image Segmentation", International Journal of Fuzzy System Applications (IJFSA), vol. 3, no. 4: IGI Global, pp. 47–59, 2013. Abstract
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Liu, H., Y. Ji, and A. E. Hassanien, "Image Color Transfer Approach by Analogy with Taylor Expansion", International Journal of System Dynamics Applications (IJSDA), vol. 2, no. 2: IGI Global, pp. 43–54, 2013. Abstract
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Liu, H., Y. Ji, and A. E. Hassanien, "Image Color Transfer Approach by Analogy with Taylor Expansion. vol. 2 issue 2, 2013", International Journal of System Dynamics Applications,, vol. 2, issue 2, pp. 43-54, 2013. AbstractWebsite

The Taylor expansion has shown in many fields to be an extremely powerful tool. In this paper, we investigated image features and their relationships by analogy with Taylor expansion. The kind of expansion could be helpful for us to analyze image feature and engraftment, such as transferring color between images. By analogy with Taylor expansion, we designed the image color transfer algorithm by the first and second-order information. The luminance histogram represents the first-order information of image, and the co-occurrence matrix represents the second-order information of image. Some results illustrate our algorithm is effective. In our study, each polynomial in our analogy Taylor expansion of images is considered as one of image features, which makes us re-understand images and its features. It provided us a cue that the features of image, such as color, texture, dimension, time series, would be not isolated but mutual relational based on image expansion.

Lamiaa M. El Bakrawy, N. I.Ghali, and A. E. Hassanien, "Intelligent Machine Learning in Image Authentication.", signal processing system, vol. 78, issue 2, pp. 223-237 , 2015. Website
Kompatsiaris, Y., S. Nikolopoulos, T. Lidy, and A. Rauber, "Media Search Cluster White Paper on" Search Computing".", ERCIM News, vol. 2012, no. 88, 2012. 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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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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Abraham, A., H. Liu, and A. E. Hassanien, "Multi swarms for neighbor selection in peer-to-peer overlay networks", Telecommunication Systems, vol. 46, no. 3: Springer Netherlands, pp. 195–208, 2011. Abstract
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Abraham, A., H. Liu, and A. E. Hassanien, "Multi swarms for neighbor selection in peer-to-peer overlay networks", Telecommunication Systems, vol. 46, no. 3: Springer Netherlands, pp. 195–208, 2011. Abstract
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Liu, H., A. Abraham, and A. E. Hassanien, "Scheduling jobs on computational grids using a fuzzy particle swarm optimization algorithm", Future Generation Computer Systems, vol. 26, no. 8: Elsevier, pp. 1336–1343, 2010. Abstract
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Conference Proceedings
Li, J., B. Dai, K. Xiao, and A. E. Hassanien, "Density Based Fuzzy Thresholding for Image Segmentation", Advanced Machine Learning Technologies and Applications (AMLTA), Cairo Egypt, pp. 118--127, 2012. Abstract3220118.pdf

In this paper, we introduce an image segmentation framework which
applies automatic threshoding selection using fuzzy set theory and fuzzy
density model. With the use of different types of fuzzy membership function,
the proposed segmentation method in the framework is applicable for images of
unimodal, bimodal and multimodal histograms. The advantages of the method
are as follows: (1) the threshoding value is automatically retrieved thus requires
no prior knowledge of the image; (2) it is not based on the minimization of a
criterion function therefore is suitable for image intensity values distributed
gradually, for example, medical images; (3) it overcomes the problem of local
minima in the conventional methods. The experimental results have
demonstrated desired performance and effectiveness of the proposed approach.

Conference Paper
Li, J., B. Dai, K. Xiao, and A. E. Hassanien, "Density based fuzzy thresholding for image segmentation", International Conference on Advanced Machine Learning Technologies and Applications: Springer Berlin Heidelberg, pp. 118–127, 2012. Abstract
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Li, J., B. Dai, K. Xiao, and A. E. Hassanien, "Density based fuzzy thresholding for image segmentation", International Conference on Advanced Machine Learning Technologies and Applications: Springer Berlin Heidelberg, pp. 118–127, 2012. Abstract
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Jui, S. - L., C. Lin, Haibing Guan, A. Abraham, A. E. Hassanien, and K. Xiao, "Fuzzy c-means with wavelet filtration for MR image segmentation", Nature and Biologically Inspired Computing (NaBIC), 2014 Sixth World Congress on: IEEE, pp. 12–16, 2014. Abstract
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Dai, G., Z. Wang, C. Yang, H. Liu, A. E. Hassanien, and W. Yang, "A multi-granularity rough set algorithm for attribute reduction through particles particle swarm optimization", Computer Engineering Conference (ICENCO), 2015 11th International: IEEE, pp. 303–307, 2015. Abstract
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Zhu, Z., Z. Wang;, T. Li;, X. Wang, H. Liu, and A. E. Hassanien, "Multi-knowledge extraction algorithm using Group Search Optimization for brain dataset analysis", 2nd International Conference on Computing for Sustainable Global Development (INDIACom) 11-13 March, pp. 1891 – 1896, , India, 11 March, 2015.
Zhu, Z., Z. Wang, T. Li, X. Wang, H. Liu, A. E. Hassanien, and W. Yang, "Multi-knowledge extraction algorithm using Group Search Optimization for brain dataset analysis", Computing for Sustainable Global Development (INDIACom), 2015 2nd International Conference on: IEEE, pp. 1891–1896, 2015. Abstract
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El-Bendary, N., O. S. Soliman, N. I. Ghali, A. E. Hassanien, V. Palade, and H. Liu, "A secure directed diffusion routing protocol for wireless sensor networks", Next Generation Information Technology (ICNIT), 2011 The 2nd International Conference on: IEEE, pp. 149–152, 2011. Abstract
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El-Bendary, N., O. S. Soliman, N. I. Ghali, A. E. Hassanien, V. Palade, and H. Liu, "A secure directed diffusion routing protocol for wireless sensor networks", Next Generation Information Technology (ICNIT), 2011 The 2nd International Conference on: IEEE, pp. 149–152, 2011. Abstract
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