B. Chandra Mohan

A Robust Image Watermarking Scheme using Singular Value Decomposition

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).

CONTENT BASED IMAGE RETRIEVAL USING EXACT LEGENDRE MOMENTS AND SUPPORT VECTOR MACHINE

Content Based Image Retrieval (CBIR) systems based on shape using invariant image moments, viz., Moment Invariants (MI) and Zernike Moments (ZM) are available in the literature. MI and ZM are good at representing the shape features of an image. However, non-orthogonality of MI and poor reconstruction of ZM restrict their application in CBIR. Therefore, an efficient and orthogonal moment based CBIR system is needed. Legendre Moments (LM) are orthogonal, computationally faster, and can represent image shape features compactly. CBIR system using Exact Legendre Moments (ELM) for gray scale images is proposed in this work. Superiority of the proposed CBIR system is observed over other moment based methods, viz., MI and ZM in terms of retrieval efficiency and retrieval time. Further, the classification efficiency is improved by employing Support Vector Machine (SVM) classifier. Improved retrieval results are obtained over existing CBIR algorithm based on Stacked Euler Vector (SERVE) combined with Modified Moment Invariants (MMI).

The performance of a hybrid routing intelligent algorithm in a mobile ad hoc network

Graphical abstractDisplay Omitted Hybrid routing intelligent algorithm is proposed in this paper.The hybrid routing intelligent algorithm improves the end-to-end delay and power consumption.The proposed hybrid routing intelligent algorithm approach has a tendency to find the optimal route. End-to-end delay, power consumption, and communication cost are some of the most important metrics in a mobile ad hoc network (MANET) when routing from a source to a destination. Recent approaches using the swarm intelligence (SI) technique proved that the local interaction of several simple agents to meet a global goal has a significant impact on MANET routing. In this work, a hybrid routing intelligent algorithm that has an ant colony optimisation (ACO) algorithm and particle swarm optimisation (PSO) is used to improve the various metrics in MANET routing. The ACO algorithm uses mobile agents as ants to identify the most feasible and best path in a network. Additionally, the ACO algorithm helps to locate paths between two nodes in a network and provides input to the PSO technique, which is a metaheuristic approach in SI. The PSO finds the best solution for a particles position and velocity and minimises cost, power, and end-to-end delay. This hybrid routing intelligent algorithm has an improved performance when compared with the simple ACO algorithm in terms of delay, power consumption, and communication cost.

IMAGE COMPRESSION AND WATERMARKING SCHEME USING SCALAR QUANTIZATION

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.

On the use of Schur Decomposition for Copyright Protection of Digital Images

This paper presents a robust image watermarking scheme for copyright protection of digital images. In this work, Schur decomposition of host image is explored for watermarking . Watermark image is embedded in the two decompositions of Schur decomposition. Schur decomposition is computationally faster and robust to image attacks than Singular Value Decomposition (SVD). Watermark image is embedded in the D component using scalar quantization. A copy of the watermark is embedded in the columns of U matrix using comparison of the coefficients with respect to the watermark image. Since same watermark is embedded in both U matrix and D matrix the robustness is improved. 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 Normalized Cross correlation (NCC) and Peak Signal to Noise Ratio (PSNR).

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

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.

Identification of cheaters in elections using steganography

Abstract This paper presents a new secret sharing scheme for identification of cheaters in the elections. In a proposed scheme secret image (voter ID) is embedded into cover image (Indian emblem) of same size and generates n stego images. The resulting stego images are visually good and look like a cover image. Various image quality metrics are used to assess the quality of stego images. Out of n stego images only last two stego images are required to reconstruct the secret and cover images without any loss. The proposed scheme offers high embedding capacity. Experimental results of proposed scheme shown to be superior in terms of PSNR and visual quality than existing schemes.AbstractThis paper presents a new secret sharing scheme for identification of cheaters in the elections. In a proposed scheme secret image (voter ID) is embedded into cover image (Indian emblem) of same size and generates n stego images. The resulting stego images are visually good and look like a cover image. Various image quality metrics are used to assess the quality of stego images. Out of n stego images only last two stego images are required to reconstruct the secret and cover images without any loss. The proposed scheme offers high embedding capacity. Experimental results of proposed scheme shown to be superior in terms of PSNR and visual quality than existing schemes.

Hybrid optimization using Ant Colony Optimization and Cuckoo Search in MANET routing

Ad hoc networks are a group of mobile nodes with wireless communication adapters which dynamically forms a temporary network. These networks do not require any existing infrastructure or network support. The lack of a central infrastructure imposes challenges, as services ensured by central infrastructure must be ensured by mobile nodes in the new environment. The network operation is decentralized as the networks organization/message delivery is effected by nodes. A Mobile Ad hoc Network (MANET) is functional in either a stand-alone manner or connected to large networks. In this work, a hybrid optimization technique using Ant Colony Optimization (ACO) and Cuckoo Search (CS) is proposed for the optimization of MANET routing. Ad hoc On-demand Distance Vector Routing (AODV) protocol is enhanced using the proposed optimization algorithm. The proposed hybrid algorithm achieves improved performance in terms of average end-to-end delay.

HVS based Robust Image Watermarking Scheme using Slant Transform

This paper presents a robust algorithm for digital image watermarking based on Human Visual System (HVS). Watermark is embedded in the Slant Transform domain by altering the transform coefficients. The perceptibility of the watermarked image using proposed algorithm is improved over DCT based algorithm9 by embedding the watermark image in selected positions based on the HVS weightage matrix. The proposed method is robust and the watermark image can survive to many image attacks like noise, bit plane removal, cropping, histogram equalization, rotation, and sharpening. Results are compared with DCT based watermarking method and found to be superior in terms of the quality of the watermarked image and resilience to attacks. The metrics used to test the robustness of the proposed algorithm are Peak Signal to Noise Ratio (PSNR) and Normalized Cross Correlation (NCC).

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

A Mobile Adhoc Network (MANET) is an assortment of mobile nodes that can establish 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 (AODV) 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.