Sushila Kamble

An effective pixel-wise fragile watermarking scheme based on ARA bits

Potential for exactly tracing maliciously altered pixels is currently desired in image authentication. This paper proposes an efficient pixel-wise fragile watermarking scheme, based on ARA (Authentication Relational & Associative) bits. In this scheme ARA bits are embedded as a watermark into the first three LSBs of each pixel of the host image. On the receiver end, by comparing the extracted LSBs and recalculated ARA bits, one can easily recognize the altered pixels of the host image.

DWT-based multiple watermarking for privacy and security of digital images in e-commerce

E-commerce has gained a wider popularity among consumers during 20th century and is one of the fastest growing segments of Internet today. However, due to openness of information on internet, security becomes an important issue. One of the solutions to this problem is digital watermarking. Multiple watermarking is an advanced digital watermarking which provides increased security and robustness as compared to singular watermarking. The existing multiple watermarking techniques lack the balance of trade off between imperceptibility, robustness and data payload. In this paper, we propose a DWT-based segmented robust spread transform watermarking technique to balance the above mentioned parameters. The use of multiple watermarks increases the embedding capacity of watermark as compared to the singular watermarking technique. Also, the spread transform disperse the watermark over a large number of frequencies providing robustness to volumetric as well as geometric distortions. The imperceptibility of watermark is good in terms of PSNR. Thus, the analytical and experimental results show that the proposed technique balances the trade off between imperceptibility, robustness and data payload.

DCT based texture watermarking using GLCM

We present a novel DCT technique for digital watermarking of textured images based on the concept of gray-level co-occurrence matrix (GLCM). We provide analysis to describe the behavior of the method in terms of correlation as a function of the offset for textured images. We compare our approach with another spatial and temporal domain watermarking techniques and demonstrate the potential for robust watermarking of textured images. From our extensive experiments, results indicate that our DCT approach is robust and secure against a wide range of image processing operations like JPEG compression, additive noise, cropping, scaling, and rotation. Also, the experimental results show that the proposed scheme has good imperceptibility.

Robust Multiple Watermarking Using Entropy Based Spread Spectrum

Nowadays; information hiding has become a significant topic of computer science due to the increasing popularity of the Internet and the essential need of data security. With respect to the general information hiding problem, a tradeoff is involved between robustness, visibility and capacity. There are many watermarking techniques and models and each of them has some advantages and disadvantages. Mostly used in conjunction with spread spectrum watermarking, perceptual shaping refers to the idea of adjusting the strength of the watermark based on the perceptual sensitivity of a region in the image. All these methods use some model that assigns weights to various regions of the image. This weight determines the strength of the watermark that is added to that part of the image. This paper offers a way of embedding watermarks in a manner that increases robustness and reduces perceptual degradation and computational complexity. After an image is segmented, the entropy is calculated for each segment and only those segments that have entropy above some thresholds are considered for watermarking. This reduces the number of segments that are watermarked thereby economizing on computation and perceptual degradation. The choice of high entropy segments ensures that the method is robust, as low entropy segments would be more sensitive to attacks.

Real Dual Tree Based Feature Variance for Face Recognition

In this paper, face recognition technique using real Dual Tree Discrete Wavelet Transform (DT-DWT) is proposed. This approach is based on local appearance feature extraction using directional multiresolution decomposition offered by real DT-DWT. It provides a local multiscale description of images with good directional selectivity, effective edge representation and invariance to shifts and in-plane rotations. The real DT-DWT is less redundant and computationally efficient. The fusion of local coefficients of detail subbands are used to extract the facial features using feature variance. The features are used for classification process using Mahalanobis distance. The technique is validated using 9 pose and 2 pose per person of ORL face dataset and 2 pose per person of YALE face dataset. The experimental results outperform traditional methods like PCA, LDA and DCT normalization.

Feature Image Generation Using Energy Distribution for Face Recognition in Transform Domain

In this paper, we propose a feature image generation method for face recognition. Feature extraction is done using three transforms viz. Discrete Cosine Transform, Slant Transform and Walsh Transform. Energy distribution defined as magnitude of effective information is used to create a feature image in transform domain by retaining high energy distribution coefficients. The proposed method consists of three steps. First, the face images are transformed into the frequency domain. Second, transformed coefficient matrix and energy distribution matrix is divided into three equal regions. Thresholds are selected in each region to retain the most significant features. Finally feature image is generated from these coefficients. Recognition is performed on generated feature images using Mahalanobis distance. Experimental results shows that the proposed method improve the face recognition rate as compared to previously proposed methods.

Multiple watermarking for copyright protection using DWT and dual-tree CWT

This paper proposes two techniques for multiple image watermarking based on discrete wavelet transform (DWT) and dual-tree complex wavelet transform (DT-CWT) using spread transform. The proposed scheme embed two watermarks by spreading the orthogonal projection vectors into the cover vectors extracted from the first level decomposition discrete wavelet coefficients in first technique and dual tree CWT coefficients of the host image in the second technique. The spread transform disperse the watermark over a large number of frequencies providing robustness to geometric attacks like rotation, scaling, cropping, etc., as well as compression like JPEG. The multiple watermark signals are embedded in different orientations of projection vectors which increase the embedding capacity as compared to the single watermark embedding techniques. The experimental results show that the watermarked image by both the techniques has good visual quality in terms of PSNR. Thus the proposed scheme provides the balanced trade off between important parameters of watermarking, i.e., capacity, robustness and imperceptibility.