Balasubramanian Raman

A new robust reference watermarking scheme based on DWT-SVD

This paper presents a new semi-blind reference watermarking scheme based on discrete wavelet transform(DWT) and singular value decomposition(SVD) for copyright protection and authenticity. We are using a gray scale logo image as watermark instead of randomly generated Gaussian noise type watermark. For watermark embedding, the original image is transformed into wavelet domain and a reference sub-image is formed using directive contrast and wavelet coefficients. We embed watermark into reference image by modifying the singular values of reference image using the singular values of the watermark. A reliable watermark extraction scheme is developed for the extraction of watermark from distorted image. Experimental evaluation demonstrates that the proposed scheme is able to withstand a variety of attacks. We show that the proposed scheme also stands with the ambiguity attack also.

A blind watermarking algorithm based on fractional Fourier transform and visual cryptography

This paper presents a robust copyright protection scheme based on fractional Fourier transform (FrFT) and visual cryptography (VC). Unlike the traditional schemes, in our scheme, the original image is not modified by embedding the watermark into the original image. We use the visual secret sharing scheme to construct two shares, namely, master share and ownership share. Features of the original image are extracted using SVD, and are used to generate the master share. Ownership share is generated with the help of secret image (watermark) and the master share, using VC technique. The two shares separately give no information about the secret image, but for ownership identification, the secret image can be revealed by stacking the master share and the ownership share. In order to achieve the robustness and security, the properties of VC, FrFT and SVD are used in our scheme. The experimental results show that the proposed scheme is strong enough to resist various signal processing operations.

Discrete fractional wavelet transform and its application to multiple encryption

The fractional wavelet transform is a useful mathematical transformation that generalizes the most prominent tool in signal and image processing namely wavelet transform by rotation of signals in the time-frequency plane. The definition of discrete fractional wavelet transform is not reported yet in the literature. Therefore, a definition of the discrete fractional wavelet transform is consolidated by discretizing continuous fractional wavelet transform in the proposed work. Possible applications of the transform are in transient signal processing, image analysis, image transmission, biometrics, image compression etc. In this paper, image transmission is chosen as the primary application and hence a novel encryption scheme is proposed for securing multiple images during communication and transmission over insecure channel. The proposed multiple image encryption scheme is consolidated by fractional wavelet transform and chaotic maps. First, all the images are encrypted followed by their sharing. The sharing process is done considering numerical techniques by making the sharing process a system of linear equations. Experimental results and security analysis demonstrate the efficiency and robustness of the proposed primary application.

Combinational domain encryption for still visual data

Image data has distinct regions of different importance. This property of image data has extensively been used to develop partial encryption techniques, but it is still unnoticed for total encryption. Providing similar security level to data of varied significance consumes more computational resources. This necessitates the development of an encryption framework that considers data significance while implementing total encryption. This article proposes a new framework of combinational domain encryption that encrypts significant data in spatial domain and insignificant data in wavelet domain. Experiments have been performed to analyze the effect of proposed framework as compared to encryption technique in a single domain. Significant reduction in computational time has been observed without compromising on the security. Medical applications or security applications requiring fast computation would be benefitted by implementation of the proposed technique.

Local extrema co-occurrence pattern for color and texture image retrieval

A real world problem of image retrieval and searching is considered in this paper. In modern generation, managing images from a large storage medium is not a straightforward job. Many researchers have worked on texture features, and produced diverse feature descriptors based on uniform, rotation invariant, edges and directional properties. However, most of them convert the relationship of the center pixel and the boundary pixel into a local pattern, and use histogram to represent the local pattern as a feature vector. In this work, we propose a new image retrieval technique; local extrema co-occurrence patterns (LECoP) using the HSV color space. HSV color space is used in this method to utilize the color, intensity and brightness of images. Local extrema patterns are applied to define the local information of image, and gray level co-occurrence matrix is used to obtain the co-occurrence of LEP map pixels. The local extrema co-occurrence pattern extracts the local directional information from local extrema pattern, and convert it into a well-mannered feature vector with use of gray level co-occurrence matrix. The presented method is tested on five standard databases called Corel, MIT VisTex and STex, in which Corel database includes Corel-1k, Corer-5k and Corel-10k databases. Also, this algorithm is compared with previous proposed methods, and results in terms of precision and recall are shown in this work.

Center symmetric local binary co-occurrence pattern for texture, face and bio-medical image retrieval

A problem of content based image retrieval is considered.A local texture feature descriptor is proposed using local pattern and GLCM.The proposed method is tested on texture, face and medical image databases.For validation, the proposed method is compared to other local patterns. Content based image retrieval is a common problem for a large image database. Many methods have been proposed for image retrieval for some particular type of datasets. In the proposed work, a new image retrieval technique has been introduced. This technique is useful for different kind of dataset. In the proposed method, center symmetric local binary pattern has been extracted from the original image to obtain the local information. Co-occurrence of pixel pairs in local pattern map have been observed in different directions and distances using gray level co-occurrence matrix. Earlier methods have utilized histogram to extract the frequency information of local pattern map but co-occurrence of pixel pairs is more robust than frequency of patterns. The proposed method is tested on three different category of images, i.e., texture, face and medical image database and compared with typical state-of-the-art local patterns.

A new robust adjustable logo watermarking scheme

In this paper, a novel, yet simple, watermarking algorithm for image authentication is proposed using fractional wavelet packet transform (FRWPT) via singular value decomposition (SVD). Unlike the traditional watermarking schemes where the watermark is added to the transform coefficients, the proposed algorithm is based on embedding in the singular values (luminance) of the host image. To improve the fidelity, the perceptual quality of the watermarked image and to enhance the security of watermarking, we model an adjustable watermarking algorithm. The meaning of the word adjustable is that the watermark is embedded into the host image by taking two watermark embedding strengths, according to owner and some cryptographic conditions. Finally, a reliable watermark extraction algorithm is developed for the extraction of watermark from the distorted image. The feasibility of this method and its robustness against different kind of attacks are verified by computer simulations and comparison with the existing work.

A New Fractional Random Wavelet Transform for Fingerprint Security

In this correspondence paper, the wavelet transform, which is an important tool in signal and image processing, has been generalized by coalescing wavelet transform and fractional random transform. The new transform, i.e., fractional random wavelet transform (FrRnWT) inherits the excellent mathematical properties of wavelet transform and fractional random transform. Possible applications of the proposed transform are in biometrics, image compression, image transmission, transient signal processing, etc. In this correspondence paper, biometrics is chosen as the primary application; and hence, a new technique is proposed for securing fingerprints during communication and transmission over insecure channel.

A new robust reference logo watermarking scheme

In this paper, a new yet simple reference logo watermarking scheme based on fractional Fourier transform (FrFT) and singular value decomposition (SVD) is proposed. The core idea of the proposed scheme is to segment host image into non-overlapping blocks by the means of Hilbert space filling curve and a reference image is formed by considering Human visual system (HVS). First, reference image is transformed into FrFT domain and embedding is done by modifying singular values of the reference image using singular values of watermark. After embedding, modified reference image is segmented into blocks and these modified blocks are mapped into their original places for constructing watermarked image. For extraction, a reliable watermark extraction scheme is proposed. The experimental results demonstrate better visual imperceptibility and resiliency of the proposed scheme against intentional or un-intentional variety of attacks.

On Demand Routing Protocols for Mobile Ad Hoc Networks: A Review

A mobile ad hoc network is a multihop wireless network with dynamically and frequently changing topology. The power, energy and bandwidth constraint of these self operating and self organized systems has made routing a challenging problem. Number of routing protocols has been developed to find routes with minimum control overhead and network resources. Extensions are done on the conventional protocols to improve the throughput by further reducing the control overhead. This paper gives an overview of the existing on demand routing protocols and a parametric comparison is made with the recently developed protocols, proposed in the literature, These protocols are the multipath extensions of Ad Hoc On Demand Distance Vector routing protocol (AODV) such as AODV with break avoidance (AODV-BR), Scalable Multipath On Demand Routing (SMORT) etc.