Colour image watermarking based on wavelet and QR decomposition

In this work, a new image watermarking algorithm on colour images is proposed. The proposed algorithm divides a cover image into three colour bands of red, green and blue. Then the following tasks are done on all three channels separately. First, Each colour band is divided into patches of small sizes then the entropy of each patch is calculated. At this step a threshold is found based on the average entropy of all patches and following is applied to all patches which have entropy lower than the threshold. A wavelet representation of each patch are given by applying a discrete wavelet transform. Then Singular value decomposition, orthogonal-triangular decomposition, and a chirp z-transform are used to embed a watermark on the cover image. Several signal processing attacks are applied on watermarked images in order to robustness of the algorithm. The Proposed algorithm is compared with one conventional and two state-of-the-art algorithms. Experimental results show superiority of the proposed algorithm compare with other algorithm in the area of image watermarking

Entropy Based Robust Watermarking Algorithm

Tänu aina kasvavale multimeedia andmeedastus mahtudele Internetis, on esile kerkinud mured turvalisusest ja piraatlusest. Digitaalse meedia paljundamise ja muutmise maht on loonud vajaduse digitaalse meedia vesimärgistamise järgi. Selles töös on tutvustatud vastupidavaid vesimärkide lisamise algoritme, mis lisavad vesimärgid madala entroopiaga pildi osadesse. Välja pakutud algoritmides jagatakse algne pilt blokkidesse ning arvutatakse iga bloki entroopia. Kõikide blokkide keskmine entroopia väärtus valitakse künniseks, mille järgi otsustatakse, millistesse blokkidesse vesimärk lisada. Kõik blokid, mille entroopia on väiksem kui künnis, viiakse signaali sageduse kujule kasutades Discrete Wavelet Transform algoritmi. Madala sagedusega sagedusvahemikule rakendatakse Chirp Z-Transform algoritmi ja saadud tulemusele LU-dekompositsiooni või QR-dekompositsiooni. Singular Value Decomposition meetodi rakendamisel diagonaalmaatriksile, mis saadi eelmisest sammust, saadakse iga bloki vastav väärtus. Vesimärk lisatakse pildile, liites iga bloki arvutatud väärtusele vesimärgi Singular Value Decomposition meetodi tulemused. Kirjeldatud algoritme testiti ning võrreldi teiste tavapärast ning uudsete vesimärkide lisamise tehnoloogiatega. Kvantitatiivsed ja kvalitatiivsed eksperimendid näitavad, et välja pakutud meetodid on tajumatud ning vastupidavad signaali töötlemise rünnakutele.With growth of digital media distributed over the Internet, concerns about security and piracy have emerged. The amount of digital media reproduction and tampering has brought a need for content watermarking. In this work, multiple robust watermarking algorithms are introduced. They embed watermark image into singular values of host image’s blocks with low entropy values. In proposed algorithms, host image is divided into blocks, and the entropy of each block is calculated. The average of all entropies indicates the chosen threshold value for selecting the blocks in which watermark image should be embedded. All blocks with entropy lower than the calculated threshold are decomposed into frequency subbands using discrete wavelet transform (DWT). Subsequently chirp z-transform (CZT) is applied to the low-frequency subband followed by an appropriate matrix decomposition such as lower and upper decomposition (LUD) or orthogonal-triangular decomposition (QR decomposition). By applying singular value decomposition (SVD) to diagonal matrices obtained by the aforementioned matrix decompositions, the singular values of each block are calculated. Watermark image is embedded by adding singular values of the watermark image to singular values of the low entropy blocks. Proposed algorithms are tested on many host and watermark images, and they are compared with conventional and other state-of-the-art watermarking techniques. The quantitative and qualitative experimental results are indicating that the proposed algorithms are imperceptible and robust against many signal processing attacks

An improved scaling factor for robust digital image watermarking scheme using DWT and SVD

As the internet has becoming very popular for digital media sharing, the digital media is easy to be accessed, downloaded and vulnerable to image processing attacks. Digital watermarking is a technique used to secure information by embedding an additional information known as watermark into the original data. The proposed scheme is approach to improve scale factor for robust image watermarking using two level of Discrete Wavelet Transform with Singular Value Decomposition. The first and second level of DWT decomposition are performed on HL and HL1 sub band respectively. One of the main contribution of this proposed approach is the decomposition of host image using two level DWT decomposition. The aim of this project primarily is to enhance the robustness of watermarking techniques by obtaining the most optimize scaling factor which increased and control the strength of watermarked image. Scale factor is a coefficient that can influence the quality and robustness of watermarked image. To achieve the research objectives, three phases of research framework are fulfilled; First phase is the analysis on scaling factor, DWT and SVD, secondly is the watermark encoding and the generation of scale factor value and lastly is the evaluation of watermarked image quality and robustness based on the scale factor. The highest PSNR recorded is 69.2112 with best scale factor 0.01. The experimental result shows significant improvement on the quality and robustness of the watermarked image using this proposed scheme

A Robust Color Image Watermarking Scheme Using Entropy and QR Decomposition

Internet has affected our everyday life drastically. Expansive volumes of information are exchanged over the Internet consistently which causes numerous security concerns. Issues like content identification, document and image security, audience measurement, ownership, copyrights and others can be settled by using digital watermarking. In this work, robust and imperceptible non-blind color image watermarking algorithm is proposed, which benefit from the fact that watermark can be hidden in different color channel which results into further robustness of the proposed technique to attacks. Given method uses some algorithms such as entropy, discrete wavelet transform, Chirp z-transform, orthogonal-triangular decomposition and Singular value decomposition in order to embed the watermark in a color image. Many experiments are performed using well-known signal processing attacks such as histogram equalization, adding noise and compression. Experimental results show that proposed scheme is imperceptible and robust against common signal processing attacks

New Digital Audio Watermarking Algorithms for Copyright Protection

This thesis investigates the development of digital audio watermarking in addressing issues such as copyright protection. Over the past two decades, many digital watermarking algorithms have been developed, each with its own advantages and disadvantages. The main aim of this thesis was to develop a new watermarking algorithm within an existing Fast Fourier Transform framework. This resulted in the development of a Complex Spectrum Phase Evolution based watermarking algorithm. In this new implementation, the embedding positions were generated dynamically thereby rendering it more difficult for an attacker to remove, and watermark information was embedded by manipulation of the spectral components in the time domain thereby reducing any audible distortion. Further improvements were attained when the embedding criteria was based on bin location comparison instead of magnitude, thereby rendering it more robust against those attacks that interfere with the spectral magnitudes. However, it was discovered that this new audio watermarking algorithm has some disadvantages such as a relatively low capacity and a non-consistent robustness for different audio files. Therefore, a further aim of this thesis was to improve the algorithm from a different perspective. Improvements were investigated using an Singular Value Decomposition framework wherein a novel observation was discovered. Furthermore, a psychoacoustic model was incorporated to suppress any audible distortion. This resulted in a watermarking algorithm which achieved a higher capacity and a more consistent robustness. The overall result was that two new digital audio watermarking algorithms were developed which were complementary in their performance thereby opening more opportunities for further research

Audio Signal Processing Using Time-Frequency Approaches: Coding, Classification, Fingerprinting, and Watermarking

Audio signals are information rich nonstationary signals that play an important role in our day-to-day communication, perception of environment, and entertainment. Due to its non-stationary nature, time- or frequency-only approaches are inadequate in analyzing these signals. A joint time-frequency (TF) approach would be a better choice to efficiently process these signals. In this digital era, compression, intelligent indexing for content-based retrieval, classification, and protection of digital audio content are few of the areas that encapsulate a majority of the audio signal processing applications. In this paper, we present a comprehensive array of TF methodologies that successfully address applications in all of the above mentioned areas. A TF-based audio coding scheme with novel psychoacoustics model, music classification, audio classification of environmental sounds, audio fingerprinting, and audio watermarking will be presented to demonstrate the advantages of using time-frequency approaches in analyzing and extracting information from audio signals.</p

Fractal-based models for internet traffic and their application to secure data transmission

This thesis studies the application of fractal geometry to the application of covert communications systems. This involves the process of hiding information in background noise; the information being encrypted or otherwise. Models and methods are considered with regard to two communications systems: (i) wireless communications; (ii) internet communications. In practice, of course, communication through the Internet cannot be disassociated from wireless communications as Internet traffic is 'piped' through a network that can include wireless communications (e.g. satellite telecommunications). However, in terms of developing models and methods for covert communications in general, points (i) and (ii) above require different approaches and access to different technologies. With regard to (i) above, we develop two methods based on fractal modulation and multi-fractal modulation. With regard to (ii), we implement a practical method and associated software for covert transmission of file attachments based on an analysis of Internet traffic noise. In both cases, however, two fractal models are considered; the first is the standard Random Scaling Fractal model and the second is a generalisation of this model that incorporates a greater range of spectral properties than the first—a Generalised Random Scaling Fractal Model. [Continues.

A performance evaluation of transform domain algorithm in watermarking based on different levels of sub-bands of discrete wavelet transform

This study proposed to evaluate the performance of transform domain algorithms in watermarking based on different level of sub bands of discrete wavelet transform (DWT) that can be used to overcome illegal copy, manipulation, distribution and reproduction of image on the network by implementing watermarking algorithm based on different levels that is low-level (LL), low- high (LH), high-low (HL), High-high (HH) and singular value decomposition (SVD) on image for their robustness, and imperceptibility. Moreover, two parameters were applied to evaluate the performance. That is, peak signal to noise ratio (PSNR) is used to measure imperceptibility of the digital image while normalize cross correlation (NCC) is applied to measure the robustness of digital image. The performance evaluations of the proposed method were implemented in MATLAB. The results showed that the described method imperceptible of HL level sub-bands than other levels of sub-bands. While the robustness is achieved by all levels sub-bands

Pengaruh Serangan LPF pada Audio Watermarking dengan Metode DWT-Histogram Terhadap Performa BER

Perkembangan teknologi yang pesat membuat kemudahan untuk mengakses data oleh umum sehingga dibutuhkan suatu perlindungan hak cipta guna melindungi hak perihal pemilikan data secara legal. Audio watermarking yang diusulkan menanamkan informasi bit biner ke dalam sebuah media digital berupa audio yang tidak menyebabkan kerusakan pada media yang disisipi informasi. Penelitian ini menggunakan kombinasi metode DWT dan Histogram. Hasil yang diperoleh berupa audio terwatermark yang mempunyai kualitas tinggi dan tidak menimbulkan dampak berati terhadap sinyal informasi yang telah disisipkan dengan menggunakan parameter Bit Error Ratio (BER). Pada penelitian ini, rata-rata BER yang didapat saat dilakukan serangan LPF adalah 0.07952. Sehingga metode ini mempunyai ketahanan yang tinggi. Sedangkan tanpa serangan watermark dapat terekstrak sempurna tanpa kerusakan dengan BER=0