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dc.contributor.authorMitashe, Mashruha Raquib
dc.contributor.authorHabib, Ahnaf Rafid Bin
dc.contributor.authorRazzaque, Anindita
dc.contributor.authorTanima, Ismat Ara
dc.contributor.authorUddin, Jia
dc.identifier.citationMitashe, M. R., Habib, A. R. B., Razzaque, A., Tanima, I. A., & Uddin, J. (2017). An adaptive digital image watermarking scheme with PSO, DWT and XFCM. Paper presented at the 2017 IEEE International Conference on Imaging, Vision and Pattern Recognition, icIVPR 2017, 10.1109/ICIVPR.2017.7890868en_US
dc.descriptionThis article was published in the IEEE Xplore [© 2017 IEEE] and the definite version is available at : The Journal's website is at:
dc.description.abstractIn this paper, a novel adaptive digital image watermarking model based on modified Fuzzy C-means clustering is proposed. For watermark embedding process, we used Discrete Wavelet Transform (DWT). A segmentation technique XieBeni integrated Fuzzy C-means clustering (XFCM) is used to identify the segments of original image to expose suitable locations for embedding watermark. We also pre-processed the host image using Particle Swarm Optimization (PSO) to lend a hand to the clustering process. The goal is to focus on proper segmentation of the image so that the embedded watermark can withstand common image processing attacks and provide security to digital images. Several attacks were performed on the watermarked images and original watermark was extracted. Performance measures like PSNR, MSE, CC were computed to test the extracted watermarks with and without attacks. Experimental results show that the proposed scheme has performed well in terms of imperceptibility and robustness when compared to other watermarking models.en_US
dc.publisher© 2017 IEEEen_US
dc.subjectDigital watermarkingen_US
dc.subjectXieBeni Indexen_US
dc.titleAn adaptive digital image watermarking scheme with PSO, DWT and XFCMen_US
dc.typeConference paperen_US
dc.contributor.departmentDepartment of Computer Science and Engineering, BRAC University

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