Tirtha Shankar Das

SVD and Neural Network Based Watermarking Scheme

Presently the WWW phenomenon has brought the world in to the personal computer. Digital media is thereby given high priority. But this has increased the frequency of security breach of intellectual properties. Therefore copyright protections and content integrity verification are highly recommended. What we need is newer data hiding techniques that must be imperceptible, robust, highly secured, etc. Digital image watermarking is one of the ways that is resilient to various attacks on the image based digital media where data authentication is done by embedding of a watermark in image characteristics. This work incorporates singular value decomposition (SVD) based image watermarking. Here unlike previous work done by researchers, error control coding (ECC) and artificial neural networks (ANN) for the authentication purposes have been used. ECC and ANN increase the robustness of the method against malicious attacks.

Robust Image Watermarking Under Pixel Wise Masking Framework

The current paper presents a robust watermarking method for still images, which uses the similarity of discrete wavelet transform and human visual system (HVS). The proposed scheme makes the use of pixel wise masking in order to make binary watermark imperceptible to the HVS. The watermark is embedded in the perceptually significant, spatially selected detail coefficients using sub band adaptive threshold scheme. The threshold is computed based on the statistical analysis of the wavelet coefficients. The watermark is embedded several times to achieve better robustness. Here, a new type of non-oblivious detection method is proposed. The improvement in robustness performance against different types of deliberate and non-intentional image impairments (lossy compression, scaling, cropping, filtering etc) is supported through experimental results. The reported result also shows improvement in visual and statistical invisibility of the hidden data. The proposed method is compared with a state of the art frequency based watermarking technique, highlighting its performance. This algorithmic architecture utilizes the existing allocated bandwidth in the data transmission channel in a more efficient manner.

An Angle QIM Watermarking in STDM Framework Robust against Amplitude Scaling Distortions

Quantization index modulation (QIM) watermarking proposed by Chen and Wornell provides computational efficient blind watermarking based on Costa’s dirty paper codes. The limitation of this is its vulnerability against amplitude scaling distortion. The present work is proposed to solve this problem based on angle QIM within spread transform dither modulation (STDM) framework. AQIM embeds the information by quantizing the angle formed by the host-signal vector with respect to the origin of a hyperspherical coordinate system as opposed to quantizing the amplitude of pixel values. It has been shown experimentally that the proposed work not only provides the resistance against this valumetric scaling distortion but also against non-linear, gamma correction and constant luminance change.

On the implementation of QIM FPGA hardware

In this paper, we propose the FPGA implementation of a watermarking algorithm in the spatial domain. The paper put emphasis on Quantization Index Modulation based watermarking approach using dither sequences. The cost-effective data embedding algorithm can conceal watermark into original cover image coming from a sensor more rapidly than software implementation and the embedded image is effortlessly transmitted to PC by using proper interface. The obtained results for the algorithm and FPGA implementation are presented and discussed.