A New Paradigm for Improved Image Steganography by using Adaptive Number of Dominant Discrete Cosine Transform Coefficients

Image steganography camouflages secret messages in images by tampering image contents. There is a natural desire for hiding maximum secret information with the least possible distortions in the host image. This requires an algorithm that intelligently optimizes the capacity keeping the required imperceptibility of the image. This paper presents an image steganography scheme that preserves an adaptively chosen block of dominant coefficients from each Discrete Cosine Transform coefficients, whereas the rest of the coefficients are replaced with normalized secret image pixel values. Secret image pixel value are normalized in an adaptively chosen range. Embedding such kind of normalized data in adaptively chosen non-square L- shaped blocks utilize maximum embedding space available in each block that consequently results in maximizing payload capacity, while maintaining the image quality. This scheme achieved payload capacity up to 21.5 bit per pixel (bpp), while maintaining image quality of 38.24 dB peak signal to noise ratio.Comment: 9 page

Semiclassical Limits of Extended Racah Coefficients

We explore the geometry and asymptotics of extended Racah coeffecients. The extension is shown to have a simple relationship to the Racah coefficients for the positive discrete unitary representation series of SU(1,1) which is explicitly defined. Moreover, it is found that this extension may be geometrically identified with two types of Lorentzian tetrahedra for which all the faces are timelike. The asymptotic formulae derived for the extension are found to have a similar form to the standard Ponzano-Regge asymptotic formulae for the SU(2) 6j symbol and so should be viable for use in a state sum for three dimensional Lorentzian quantum gravity.Comment: Latex2e - 26 pages, 6 figures. Uses AMS-fonts, AMS-LaTeX, epsf.tex and texdraw. Revised version with improved clarity and additional result

Word Embedding based Correlation Model for Question/Answer Matching

With the development of community based question answering (Q&A) services, a large scale of Q&A archives have been accumulated and are an important information and knowledge resource on the web. Question and answer matching has been attached much importance to for its ability to reuse knowledge stored in these systems: it can be useful in enhancing user experience with recurrent questions. In this paper, we try to improve the matching accuracy by overcoming the lexical gap between question and answer pairs. A Word Embedding based Correlation (WEC) model is proposed by integrating advantages of both the translation model and word embedding, given a random pair of words, WEC can score their co-occurrence probability in Q&A pairs and it can also leverage the continuity and smoothness of continuous space word representation to deal with new pairs of words that are rare in the training parallel text. An experimental study on Yahoo! Answers dataset and Baidu Zhidao dataset shows this new method's promising potential.Comment: 8 pages, 2 figure

Implementation and Analysis of Information Hiding Techniques Using DCT and Neural Network

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Watermarking for multimedia security using complex wavelets

This paper investigates the application of complex wavelet transforms to the field of digital data hiding. Complex wavelets offer improved directional selectivity and shift invariance over their discretely sampled counterparts allowing for better adaptation of watermark distortions to the host media. Two methods of deriving visual models for the watermarking system are adapted to the complex wavelet transforms and their performances are compared. To produce improved capacity a spread transform embedding algorithm is devised, this combines the robustness of spread spectrum methods with the high capacity of quantization based methods. Using established information theoretic methods, limits of watermark capacity are derived that demonstrate the superiority of complex wavelets over discretely sampled wavelets. Finally results for the algorithm against commonly used attacks demonstrate its robustness and the improved performance offered by complex wavelet transforms

Resilient Digital Image Watermarking Using a DCT- Component Perturbation Model

The applications of the Discrete Cosine Transform (DCT) for Computer Generated Imagery, image processingand, in particular, image compression are well known and the DCT also forms the central kernel for a number ofdigital image watermarking methods. In this paper we consider the application of the DCT for producing a highlyrobust method of watermarking images using a block partitioning approach subject to a self-alignment strategyand bit error correction. The applications for the algorithms presented include the copyright protection of imagesand Digital Right Management for image libraries, for example. However, the principal focus of the researchreported in this paper is on the use of print-scan and e-display-scan image authentication for use in e-ticketswhere QR code, for example, are embedded in an full colour image of the ticket holder. This requires that a DCTembedding procedure is developed that is highly robust to blur, noise, geometric distortions such as rotation, shift and barrel and the partial removal of image segments, all of which are consider ed in regard to the resilience of the method proposed and its practical realisation in a real operating environment