A survey on applications and variants of the cuckoo search algorithm

http://lms.ctl.cyut.edu.tw/sysdata/8/21108/doc/d7b84166985e286b/attach/905844.pdf

A digital watermarking scheme based on singular value decomposition and tiny genetic algorithm

This paper presents a robust image watermarking scheme for multimedia copyright protection. In this work, host image is partitioned into four sub images. Watermark image such as ‘logo’ is embedded in the two of these sub images, in both D (singular and diagonal matrix) and U (left singular and orthogonal matrix) components of Singular Value Decomposition (SVD) of two sub images. Watermark image is embedded in the D component using Dither quantization. A copy of the watermark is embedded in the columns of U matrix using comparison of the coefficients of U matrix with respect to the watermark image. If extraction of watermark from D matrix is not complete, there is a fair amount of probability that it can be extracted from U matrix. The proposed algorithm is more secure and robust to various attacks, viz., JPEG2000 compression, JPEG compression, rotation, scaling, cropping, row-column blanking, row-column copying, salt and pepper noise, filtering and gamma correction. Superior experimental results are observed with the proposed algorithm over a recent scheme proposed by Chung et al. in terms of Bit Error Rate (BER), Normalized Cross correlation (NC) and Peak Signal to Noise Ratio (PSNR).

A Robust Image Watermarking Scheme using Singular Value Decomposition

Various content-based image retrieval techniques are available for retrieving the require and classify images, we are reviewing them. In our first section, we are tending towards some basics of a particular CBIR system with that we have shown some basic features of any image, these are like shape, texture, color and shown different techniques to calculate them. In the next section, we have shown different distance measuring techniques used for similarity measurement of any image and also discussed indexing techniques. Finally conclusion and future scope is discussed.

A Survey on Content Based Image Retrieval Systems

In the past decade, several schemes for digital image watermarking have been proposed to protect the copyright of an image document or to provide proof of ownership in some identifiable fashion. This paper proposes a novel multiplicative watermarking scheme in the contourlet domain. The effectiveness of a watermark detector depends highly on the modeling of the transform-domain coefficients. In view of this, we first investigate the modeling of the contourlet coefficients by the alpha-stable distributions. It is shown that the univariate alpha-stable distribution fits the empirical data more accurately than the formerly used distributions, such as the generalized Gaussian and Laplacian, do. We also show that the bivariate alpha-stable distribution can capture the across scale dependencies of the contourlet coefficients. Motivated by the modeling results, a blind watermark detector in the contourlet domain is designed by using the univariate and bivariate alpha-stable distributions. It is shown that the detectors based on both of these distributions provide higher detection rates than that based on the generalized Gaussian distribution does. However, a watermark detector designed based on the alpha-stable distribution with a value of its parameter α other than 1 or 2 is computationally expensive because of the lack of a closed-form expression for the distribution in this case. Therefore, a watermark detector is designed based on the bivariate Cauchy member of the alpha-stable family for which α = 1 . The resulting design yields a significantly reduced-complexity detector and provides a performance that is much superior to that of the GG detector and very close to that of the detector corresponding to the best-fit alpha-stable distribution. The robustness of the proposed bivariate Cauchy detector against various kinds of attacks, such as noise, filtering, and compression, is studied and shown to be superior to that of the generalized Gaussian detector.

A study of multiplicative watermark detection in the contourlet domain using alpha-stable distributions.

This paper presents a new compression technique and image watermarking algorithm based on Contourlet Transform (CT). For image compression, an energy based quantization is used. Scalar quantization is explored for image watermarking. Double filter bank structure is used in CT. The Laplacian Pyramid (LP) is used to capture the point discontinuities, and then followed by a Directional Filter Bank (DFB) to link point discontinuities. The coefficients of down sampled low pass version of LP decomposed image are re-ordered in a pre-determined manner and prediction algorithm is used to reduce entropy (bits/pixel). In addition, the coefficients of CT are quantized based on the energy in the particular band. The superiority of proposed algorithm to JPEG is observed in terms of reduced blocking artifacts. The results are also compared with wavelet transform (WT). Superiority of CT to WT is observed when the image contains more contours. The watermark image is embedded in the low pass image of contourlet decomposition. The watermark can be extracted with minimum error. In terms of PSNR, the visual quality of the watermarked image is exceptional. The proposed algorithm is robust to many image attacks and suitable for copyright protection applications.

Image Compression and Watermarking scheme using Scalar Quantization

/pdf/image-compression-and-watermarking-scheme-using-scalar-409eol8gk6.pdf

Image compression and watermarking scheme using scalar quantization

an adhoc network without any centralized structures. Networking infrastructure such as the base stations is unavailable for MANET. The interconnected collection of wireless nodes depends on its position and, its transmitting and receiving radio capacity to create a wireless connectivity and form a multi-hop graph or an "adhoc" network. Routing in MANET is used for finding the multi-hop paths to transmit the data flow through the network while optimizing one or more performance measures. In this paper, modified Ant Colony Optimization (ACO) has been proposed for the optimization for MANET routing protocol. The modifications have been incorporated in Adhoc On-demand Distance Vector (AODy) routing. The proposed modified Ant Colony Optimization algorithm performs better compared to existing algorithms(AODV and Cooperative Opportunistic Routing in Mobile Adhoc Networks i.e. CORMAN) in terms of end-to-end delay, route acquisition time, throughput, total cache replies and packet delivery ratio.

Modified Ant Colony Optimization to Enhance MANET Routing in Adhoc on Demand Distance Vector

The RF band pass filters are important for wireless communication applications. They can be realized using Thin Film Bulk Acoustic Resonator (TFBAR).TFBAR is designed using Aluminium Nitride (AlN) and electrodes of piezoelectric material are made with Platinum (Pt).Various modelling techniques has been used for realizing three layered TFBAR structure. Modified Butter worth-van Dyke model (MBVD) is one used for numerical simulation of AlN film and thin electrodes. The result shows that Lm, Cm, Rm and Co model is perfectly applicable for predicting the response of TFBAR. The proposed design is realized by connecting three series and two shunt FBARs in ladder configuration. In the present work, the filter has been designed for a bandwidth of 270 MHz at -3 dB. The minimum insertion loss of -0.9 dB and return loss of -25 dB are obtained for VSWR ≤ 2 at resonance frequency.

/pdf/design-and-analysis-of-film-bulk-acoustic-resonator-fbar-1kkh3upcev.pdf

Design and Analysis of Film Bulk Acoustic Resonator (FBAR) Filter for RF Applications

Digital watermarking is a technique for protecting the copyright of intellectual property. In the recent past, several watermarking schemes have been proposed that modify pixel intensity values or coefficient values in transform domain. The popular transform domains are DCT, DFT, DWT and Singular Value Decomposition (SVD). This paper presents a highly robust and oblivious digital image watermarking scheme, in the SVD domain using dither quantization. SVD of a given image block results in three matrices [U D V]. The proposed method integrates the approach of SVD based digital watermarking scheme and dither quantization. Dither quantization, a variant of Quantization Index Modulation (QIM) is used to modify the largest component of Diagonal Matrix (D) for watermark embedding. The proposed algorithm is more secure for data hiding and robust to various attacks, viz., JPEG2000 compression, JPEG compression, rotation, scaling, cropping, row-column blanking, row-column copying, salt & pepper noise, filtering, gamma correction and image tampering. Superior experimental results are observed in the proposed algorithm over Sun et al. scheme [1]. Normalized cross correlation (NC) and Peak Signal to Noise Ratio (PSNR) are used to test and verify the robustness of the proposed algorithm.

B. Chandra Mohan

Papers

Image Compression and Watermarking scheme using Scalar Quantization

Image compression and watermarking scheme using scalar quantization

Modified Ant Colony Optimization to Enhance MANET Routing in Adhoc on Demand Distance Vector

Design and Analysis of Film Bulk Acoustic Resonator (FBAR) Filter for RF Applications

An oblivious image watermarking scheme using singular value decomposition