A New Digital Watermarking Algorithm Using Combination of Least Significant Bit (LSB) and Inverse Bit

In this paper, we introduce a new digital watermarking algorithm using least significant bit (LSB). LSB is used because of its little effect on the image. This new algorithm is using LSB by inversing the binary values of the watermark text and shifting the watermark according to the odd or even number of pixel coordinates of image before embedding the watermark. The proposed algorithm is flexible depending on the length of the watermark text. If the length of the watermark text is more than ((MxN)/8)-2 the proposed algorithm will also embed the extra of the watermark text in the second LSB. We compare our proposed algorithm with the 1-LSB algorithm and Lee's algorithm using Peak signal-to-noise ratio (PSNR). This new algorithm improved its quality of the watermarked image. We also attack the watermarked image by using cropping and adding noise and we got good results as well.Comment: 8 pages, 6 figures and 4 tables; Journal of Computing, Volume 3, Issue 4, April 2011, ISSN 2151-961

Towards video streaming in IoT environments: vehicular communication perspective

Multimedia oriented Internet of Things (IoT) enables pervasive and real-time communication of video, audio and image data among devices in an immediate surroundings. Today's vehicles have the capability of supporting real time multimedia acquisition. Vehicles with high illuminating infrared cameras and customized sensors can communicate with other on-road devices using dedicated short-range communication (DSRC) and 5G enabled communication technologies. Real time incidence of both urban and highway vehicular traffic environment can be captured and transmitted using vehicle-to-vehicle and vehicle-to-infrastructure communication modes. Video streaming in vehicular IoT (VSV-IoT) environments is in growing stage with several challenges that need to be addressed ranging from limited resources in IoT devices, intermittent connection in vehicular networks, heterogeneous devices, dynamism and scalability in video encoding, bandwidth underutilization in video delivery, and attaining application-precise quality of service in video streaming. In this context, this paper presents a comprehensive review on video streaming in IoT environments focusing on vehicular communication perspective. Specifically, significance of video streaming in vehicular IoT environments is highlighted focusing on integration of vehicular communication with 5G enabled IoT technologies, and smart city oriented application areas for VSV-IoT. A taxonomy is presented for the classification of related literature on video streaming in vehicular network environments. Following the taxonomy, critical review of literature is performed focusing on major functional model, strengths and weaknesses. Metrics for video streaming in vehicular IoT environments are derived and comparatively analyzed in terms of their usage and evaluation capabilities. Open research challenges in VSV-IoT are identified as future directions of research in the area. The survey would benefit both IoT and vehicle industry practitioners and researchers, in terms of augmenting understanding of vehicular video streaming and its IoT related trends and issues

Information Browsing via Diagram Displays

In visual information processing diagrams are frequently used for representing information. In large scale systems this results in very large diagrams and raises the questions of how to best display such diagrams on a computer screen and how to navigate around the diagrams.The aim of this research is to develop a system for automatic navigation of large diagrams. To display the diagram we are using a distortion oriented display technique. This shows the overall structure in outline form, but the particular area of interest in sufficient detail. Our navigation system is based on reasoning and making inferences. By automatic navigation we mean that the focused viewpoint is moved automatically along a navigation path. Using a clue set provided visually by the user the diagram is traversed following some navigation path. We are currently developing a prototype system

Target Acquisition in Multiscale Electronic Worlds

Since the advent of graphical user interfaces, electronic information has grown exponentially, whereas the size of screen displays has stayed almost the same. Multiscale interfaces were designed to address this mismatch, allowing users to adjust the scale at which they interact with information objects. Although the technology has progressed quickly, the theory has lagged behind. Multiscale interfaces pose a stimulating theoretical challenge, reformulating the classic target-acquisition problem from the physical world into an infinitely rescalable electronic world. We address this challenge by extending Fitts’ original pointing paradigm: we introduce the scale variable, thus defining a multiscale pointing paradigm. This article reports on our theoretical and empirical results. We show that target-acquisition performance in a zooming interface must obey Fitts’ law, and more specifically, that target-acquisition time must be proportional to the index of difficulty. Moreover, we complement Fitts’ law by accounting for the effect of view size on pointing performance, showing that performance bandwidth is proportional to view size, up to a ceiling effect. The first empirical study shows that Fitts’ law does apply to a zoomable interface for indices of difficulty up to and beyond 30 bits, whereas classical Fitts’ law studies have been confined in the 2-10 bit range. The second study demonstrates a strong interaction between view size and task difficulty for multiscale pointing, and shows a surprisingly low ceiling. We conclude with implications of these findings for the design of multiscale user interfaces

(Focus+context)3: distortion-oriented displays in three dimensions

3D datasets are becoming increasingly common, especially the use of large 3D datasets in geographical information systems (GIS) applications. Similar problems are likely with 3D datasets as have been found with large 2D datasets; namely the loss of context when examining a particular area of the data in detail. This paper proposes a solution based on 3D distortion-oriented displays, building on previous work on such displays for 2D datasets. Two such 3D distortion-oriented displays are described: the 3D Cartesian fisheye display and the 3D polar fisheye display. These displays are tested with a very small 3D dataset as a proof of concept, and it is proposed that their operation should be examined when applied to large datasets