Template based image watermarking in the fractional fourier domain

Gökozan, Tolga
One of the main features of digital technology is that the digital media can be duplicated and reproduced easily. However, this allows unauthorized and illegal use of information, i.e. data piracy. To protect digital media against illegal attempts a signal, called watermark, is embedded into the multimedia data in a robust and invisible manner. A watermark is a short sequence of information, which contains owner2s identity. It is used for evidence of ownership and copyright purposes. In this thesis, we use fractional Fourier transformation (FrFT) domain, which combines space and spatial frequency domains, for watermark embedding and implement well-known secure spread spectrum watermarking approach. However, the spread spectrum watermarking scheme is fragile against geometrical attacks such as rotation and scaling. To gain robustness against geometrical attacks, an invisible template is inserted into the watermarked image in Fourier transformation domain. The template contains no information in itself but it is used to detect the transformations undergone by the image. Once the template is detected, these transformations are inverted and the watermark signal is decoded. Watermark embedding is performed by considering the masking characteristics of the Human Visual System, to ensure the watermark invisibility. In addition, we implement watermarking algorithms, which use different transformation domains such as discrete cosine transformation domain, discrete Fourier transformation domain and discrete wavelet transformation domain for watermark embedding. The performance of these algorithms and the FrFT domain watermarking scheme is experimented against various attacks and distortions, and their robustness are compared.


StreamMARS: A Streaming Multivariate Adaptive Regression Splines Algorithm
Batmaz, İnci (2019-12-14)
Computers and internet have become inevitable parts of our life in the 1990s, and afterwards, bulk of data are started being recorded in digital platforms automatically. To extract meaningful patterns from such data computational methods are developed in data mining and machine learning domains. Multivariate adaptive regression splines (MARS) is one such method successfully applied to off-line static data for prediction. In about last ten years, we face with the big data problem due to the steady increase i...
Design and implementation of a novel visual analysis system for image clasiffication
Altintakan, Ümit Lütfü; Yazıcı, Adnan; Körpeoğlu, İbrahim; Department of Computer Engineering (2013)
Possibilities offered by the technology to create, share and disseminate image and video data have resulted in a rapid increase in the available visual data. However, the data is useless unless it is effectively accessed, which necessitates the semantic analysis of visual data. In this dissertation, we present a novel visual analysis system along with its application to image classification problem. We aim to address the challenges in the area originated from the semantic gap, and to facilitate the research...
Comparison of domain-independent and domain-specific location predictors with campus-wide Wi-Fi mobility data
Karakoç, Mücahit; Coşar, Ahmet; Bayır, Murat Ali; Department of Computer Engineering (2010)
In mobile computing systems, predicting the next location of a mobile wireless user has gained interest over the past decade. Location prediction may have a wide-range of application areas such as network load balancing, advertising and web page prefetching. In the literature, there exist many location predictors which are divided into two main classes: domain-independent and domain-specific. Song et al. compare the prediction accuracy of the domain-independent predictors from four major families, namely, M...
Composite Method in Real Time Video Stabilization
Bayrak, Serhat; Ulusoy, İlkay (2009-01-01)
Since digital video stabilization completely performs over the images, if requires exhaustive processing power. Therefore, it is less preferred for real-time applications. Global (background) motion estimation in floating video is the most time consuming part of digital video stabilization. In this work, the load of digital motion estimation is reduced by using mechanical motion sensors, thus, it is shown that digital video stabilization can be used for real-time applications.
Flexible querying using structural and event based multimodal video data model
Oztarak, Hakan; Yazıcı, Adnan (2006-01-01)
Investments on multimedia technology enable us to store many more reflections of the real world in digital world as videos so that we carry a lot of information to the digital world directly. In order to store and efficiently query this information, a video database system (VDBS) is necessary. We propose a structural, event based and multimodal (SEBM) video data model which supports three different modalities that are visual, auditory and textual modalities for VDBSs and we can dissolve these three modaliti...
Citation Formats
T. Gökozan, “Template based image watermarking in the fractional fourier domain,” M.S. - Master of Science, Middle East Technical University, 2005.