Spread spectrum-based video watermarking algorithms for copyright protection

Merged with duplicate record 10026.1/2263 on 14.03.2017 by CS (TIS)Digital technologies know an unprecedented expansion in the last years. The consumer can now benefit from hardware and software which was considered state-of-the-art several years ago. The advantages offered by the digital technologies are major but the same digital technology opens the door for unlimited piracy. Copying an analogue VCR tape was certainly possible and relatively easy, in spite of various forms of protection, but due to the analogue environment, the subsequent copies had an inherent loss in quality. This was a natural way of limiting the multiple copying of a video material. With digital technology, this barrier disappears, being possible to make as many copies as desired, without any loss in quality whatsoever. Digital watermarking is one of the best available tools for fighting this threat. The aim of the present work was to develop a digital watermarking system compliant with the recommendations drawn by the EBU, for video broadcast monitoring. Since the watermark can be inserted in either spatial domain or transform domain, this aspect was investigated and led to the conclusion that wavelet transform is one of the best solutions available. Since watermarking is not an easy task, especially considering the robustness under various attacks several techniques were employed in order to increase the capacity/robustness of the system: spread-spectrum and modulation techniques to cast the watermark, powerful error correction to protect the mark, human visual models to insert a robust mark and to ensure its invisibility. The combination of these methods led to a major improvement, but yet the system wasn't robust to several important geometrical attacks. In order to achieve this last milestone, the system uses two distinct watermarks: a spatial domain reference watermark and the main watermark embedded in the wavelet domain. By using this reference watermark and techniques specific to image registration, the system is able to determine the parameters of the attack and revert it. Once the attack was reverted, the main watermark is recovered. The final result is a high capacity, blind DWr-based video watermarking system, robust to a wide range of attacks.BBC Research & Developmen

Watermarking for multimedia security using complex wavelets

This paper investigates the application of complex wavelet transforms to the field of digital data hiding. Complex wavelets offer improved directional selectivity and shift invariance over their discretely sampled counterparts allowing for better adaptation of watermark distortions to the host media. Two methods of deriving visual models for the watermarking system are adapted to the complex wavelet transforms and their performances are compared. To produce improved capacity a spread transform embedding algorithm is devised, this combines the robustness of spread spectrum methods with the high capacity of quantization based methods. Using established information theoretic methods, limits of watermark capacity are derived that demonstrate the superiority of complex wavelets over discretely sampled wavelets. Finally results for the algorithm against commonly used attacks demonstrate its robustness and the improved performance offered by complex wavelet transforms

Digital Audio Watermarking Dengan Algoritma Wavelet Transform dan Complex Cepstrum Transform<br>Digital Audio Watermarking Using Wavelet Transform and Complex Cepstrum Transform

ABSTRAKSI: Pada Tugas Akhir ini penulis membuat sebuah system audio watermarking dengan judul “Digital Audio Watermarking dengan Algoritma Wavelet Transform dan Complex Cepstrum Transform”. Audio watermarking merupakan suatu cara untuk memberikan perlindungan terhadap file audio dan dilakukan dengan cara menyisipkan data yang diinginkan, dan pada tugas akhir ini data yang disisipkan adalah image biner.Sistem watermarking ini menggunakan analisa cepstral complex, Analisa cepstral kompleks adalah pemetaan homomorphic dan merupakan metoda ekstraksi paling efektif dalam identifikasi audio. Pada metoda ini, suatu urutan pseudo-random digunakan untuk memberi watermarking pada sinyal audio. Watermark ini kemudian dirubah ke dalam domain cepstrum distribusi koefisien cepstral dan karakteristik frekuensi masking dari HAS.P engujian dilakukan dengan dua cara yaitu secara objektif dan secara subjektif. Pengujian secara objektif dengan menggunakan Signal to Noise Ratio (SNR), Mean Square Error (MSE) dan Normalized Correlation (NC) serta secara subjektif dengan menggunakan Mean Opinion Score (MOS). Dengan SNR yang dihasilkan mencapai 55,4821 dB, nilai MSE yang dihasilkan mencapai 9,45x10-8. Sedangkan untuk penilaian secara subjektif mencapai rata-rata 4,65 atau dapat dikatakan excellent. Pada system ini juga diberikan serangan untuk menunjukkan kualitas dari audio watermarking yang di buat, yaitu dengan penambahan sinyal AWGN.Kata Kunci : watermarking, wavelet transform dan cepstrum transform.ABSTRACT: In this Final Project created a Digital watermarking audio system with the title “Didital Audio Watermarking with Wavelet Transform Algorithm and Complex Cepstrum Transform”. Audio Digital watermarking is a way to provide protection for audio files and is done by inserting the desired data, and the final task of this data is a binary image.The system of Watermarking use the complex cepstral analysis. The complex cepstral analysis is a homomorphic mapping and is the most effective extractionmethod in audio identification. In this method, a pseudo-random sequence was used to watermark the audio signal. The watermark is then weighted in the cepstrum domain according to the distribution of cepstral coefficients and the frequency masking characteristics of HAS.Two kinds of tests done to prove the capability of this Digital Watermarking, which is an objective test using Signal to Noise ratio (SNR), Mean Square Error (MSE) and Normalized Correlation (NC) and subjectively by using the Mean Opinion Score (MOS). With the resulting SNR achieved 55,4821 dB and the resulting MSE achieved 9,45x10-8. Whereas for the subjective assessment of the average reached 4,65, or can say excellent. In this system also provided the attacks to demonstrate the quality of the audio Digital watermarking is made, the attack is additive white Gauss noise (AWGN).Keyword: watermarking, wavelet transform dan cepstrum transform