Blind audio watermarking technique based on two dimensional cellular automata

In this paper we propose a new method of digital audio watermarking based on two dimensional cellular automata; the method increases the dimension of the audio and uses cellular automata in generating the key of watermark embedding. The watermarking method is blind, and does not require the original host audio or any of its features to extract the watermark; the watermark can be easily extracted using the right key. The experimental results show that the watermarks are imperceptible; and show a high similarity between the original and the watermarked audio. Cosine similarity and peak signal-to-noise ratio were used to measure the similarity between the original audio and the watermarked audio

The framework of P systems applied to solve optimal watermarking problem

Membrane computing (known as P systems) is a novel class of distributed parallel computing models inspired by the structure and functioning of living cells and organs, and its application to the real-world problems has become a hot topic in recent years. This paper discusses an interesting open problem in digital watermarking domain, optimal watermarking problem, and proposes a new optimal image watermarking method under the framework of P systems. A special membrane structure is designed and its cells as parallel computing units are used to find the optimal watermarking parameters for image blocks. Some cells use the position-velocity model to evolve watermarking parameters of image blocks, while another cell evaluates the objects in the system. In addition to the evolution rules, communication rules are used to exchange and share information between the cells. Simulation experiments on large image set compare the proposed framework with other existing watermarking methods and demonstrate its superiority.National Natural Science Foundation of China No 61170030Chunhui Project Foundation of the Education Department of China No. Z2012025Chunhui Project Foundation of the Education Department of China No. Z2012031Sichuan Key Technology Research and Development Program No. 2013GZX015

DIGITAL WATERMARKING OF 3D MEDICAL VISUAL OBJECTS

At present, medical equipment provides often 3D models of scanning organs instead of ordinary 2D images. This concept is supported by Digital Imaging and COmmunications in Medicine (DICOM) standard available for telemedicine. This means that the confidential information under transmission ought to be protected by special techniques, particularly digital watermarking scheme instead of textual informative files represented, for example, on CD disks. We propose a multilevel protection, for which a fragile watermark is the first level of protection. The Region Of Interest (ROI) watermark and textual watermarks with information about patient and study (the last ones can be combines as a single textual watermark) form the second level of protection. Encryption of the ROI and textual watermarks using Arnold’s transform is the third level of protection. In the case of 3D models, we find the ROI in each of 2D sliced images, apply the digital wavelet transform or digital shearlet transform (depending on the volume of watermarks) for the ROI and textual watermarks embedding, and embed a fragile watermark using digital Hadamard transform. The main task is to find the relevant regions for embedding. To this and, we develop the original algorithm for selecting relevant regions. The obtained results confirm the robustness of our approach for rotation, scaling, translation, and JPEG attacks

반향 환경에 강인한 음향 데이터 전송을 위한 오디오 정보 은닉 기법 연구

학위논문 (박사)-- 서울대학교 대학원 : 전기·컴퓨터공학부, 2014. 2. 김남수.In this dissertation, audio data hiding methods suitable for acoustic data transmission are studied. Acoustic data transmission implies a technique which communicates data in short-range aerial space between a loudspeaker and a microphone. Audio data hiding method implies a technique that embeds message signals into audio such as music or speech. The audio signal with embedded message is played back by the loudspeaker at a transmitter and the signal is recorded by the microphone at a receiver without any additional communication devices. The data hiding methods for acoustic data transmission require a high level of robustness and data rate than those for other applications. For one of the conventional methods, the acoustic orthogonal frequency division multiplexing (AOFDM) technique was developed as a reliable communication with reasonable bit rate. The conventional methods including AOFDM, however, are considered deficient in transmission performance or audio quality. To overcome this limitation, the modulated complex lapped transform (MCLT) is introduced in the second chapter of the dissertation. The system using MCLT does not produce blocking artifacts which may degrade the quality of the resulting data-embedded audio signal. Moreover, the interference among adjacent coefficients due to the overlap property is analyzed to take advantage of it for data embedding and extraction. In the third chapter of the dissertation, a novel audio data hiding method for the acoustic data transmission using MCLT is proposed. In the proposed system, audio signal is transformed by the MCLT and the phases of the coefficients are modified to embed message based on the fact that human auditory perception is more sensitive to the variation in magnitude spectra. In the proposed method, the perceived quality of the data-embedded audio signal can be kept almost similar to that of the original audio while transmitting data at several hundreds of bits per second (bps). The experimental results have shown that the audio quality and transmission performance of proposed system are better than those of the AOFDM based system. Moreover, several techniques have been found to further improve the performance of the proposed acoustic data transmission system which are listed as follows: incorporating a masking threshold (MM), clustering based decoding (CLS), and a spectral magnitude adjustment (SMA). In the fourth chapter of the dissertation, an audio data hiding technique more suitable for acoustic data transmission in reverberant environments is proposed. In this approach, sophisticated techniques widely deployed in wireless communication is incorporated which can be summarized as follows: First, a proper range of MCLT length to cope with reverberant environments is analyzed based on the wireless communication theory. Second, a channel estimation technique based on the Wiener estimator to compensate the effect of channel is applied in conjunction with a suitable data packet structure. From the experimental result, the MCLT length longer than the reverberation time is found to be robust against the reverberant environments at the cost of the quality of the data-embedded audio. The experimental results have also shown that the proposed method is robust against various forms of attacks such as signal processing, overwriting, and malicious removal methods. However, it would be the most severe problem to find a proper window length which satisfies both the inaudible distortion and robust data transmission in the reverberant environments. For the phase modification of the audio signal, it would be highly likely to incur a significant quality degradation if the length of time-frequency transform is very long due to the pre-echo phenomena. In the fifth chapter, therefore, segmental SNR adjustment (SSA) technique is proposed to further modify the spectral components for attenuating the pre-echo. In the proposed SSA technique, segmenatal SNR is calculated from short-length MCLT analysis and its minimum value is limited to a desired value. The experimental results have shown that the SSA algorithm with a long MCLT length can attenuate the pre-echo effectively such that it can transmit data more reliably while preserving good audio quality. In addition, a good trade-off between the audio quality and transmission performance can be achieved by adjusting only a single parameter in the SSA algorithm. If the number of microphones is more than one, the diversity technique which takes advantage of transmitting duplicates through statistically independent channel could be useful to enhance the transmission reliability. In the sixth chapter, the acoustic data transmission technique is extended to take advantage of the multi-microphone scheme based on combining. In the combining-based multichannel method, the synchronization and channel estimation are respectively performed at each received signal and then the received signals are linearly combined so that the SNR is increased. The most noticeable property for combining-based technique is to provide compatibility with the acoustic data transmission system using a single microphone. From the series of the experiments, the proposed multichannel method have been found to be useful to enhance the transmission performance despite of the statistical dependency between the channels.Abstract i List of Figures ix List of Tables xv Chapter 1 Introduction 1 1.1 Audio Data Hiding and Acoustic Data Transmission 1 1.2 Previous Methods 4 1.2.1 Audio Watermarking Based Methods 4 1.2.2 Wireless Communication Based Methods 6 1.3 Performance Evaluation 9 1.3.1 Audio Quality 9 1.3.2 Data Transmission Performance 10 1.4 Outline of the Dissertation 10 Chapter 2 Modulated Complex Lapped Transform 13 2.1 Introduction 13 2.2 MCLT 14 2.3 Fast Computation Algorithm 18 2.4 Derivation of Interference Terms in MCLT 19 2.5 Summary 24 Chapter 3 Acoustic Data Transmission Based on MCLT 25 3.1 Introduction 25 3.2 Data Embedding 27 3.2.1 Message Frame 27 3.2.2 Synchronization Frame 29 3.2.3 Data Packet Structure 32 3.3 Data Extraction 32 3.4 Techniques for Performance Enhancement 33 3.4.1 Magnitude Modification Based on Frequency Masking 33 3.4.2 Clustering-based Decoding 35 3.4.3 Spectral Magnitude Adjustment Algorithm 37 3.5 Experimental Results 39 3.5.1 Comparison with Acoustic OFDM 39 3.5.2 Performance Improvements by Magnitude Modification and Clustering based Decoding 47 3.5.3 Performance Improvements by Spectral Magnitude Adjustment 50 3.6 Summary 52 Chapter 4 Robust Acoustic Data Transmission against Reverberant Environments 55 4.1 Introduction 55 4.2 Data Embedding 56 4.2.1 Data Embedding 57 4.2.2 MCLT Length 58 4.2.3 Data Packet Structure 60 4.3 Data Extraction 61 4.3.1 Synchronization 61 4.3.2 Channel Estimation and Compensation 62 4.3.3 Data Decoding 65 4.4 Experimental Results 66 4.4.1 Robustness to Reverberation 69 4.4.2 Audio Quality 71 4.4.3 Robustness to Doppler Effect 71 4.4.4 Robustness to Attacks 71 4.5 Summary 75 Chapter 5 Segmental SNR Adjustment for Audio Quality Enhancement 77 5.1 Introduction 77 5.2 Segmental SNR Adjustment Algorithm 79 5.3 Experimental Results 83 5.3.1 System Configurations 83 5.3.2 Audio Quality Test 84 5.3.3 Robustness to Attacks 86 5.3.4 Transmission Performance of Recorded Signals in Indoor Environment 87 5.3.5 Error correction using convolutional coding 89 5.4 Summary 91 Chapter 6 Multichannel Acoustic Data Transmission 93 6.1 Introduction 93 6.2 Multichannel Techniques for Robust Data Transmission 94 6.2.1 Diversity Techniques for Multichannel System 94 6.2.2 Combining-based Multichannel Acoustic Data Transmission 98 6.3 Experimental Results 100 6.3.1 Room Environments 101 6.3.2 Transmission Performance of Simulated Environments 102 6.3.3 Transmission Performance of Recorded Signals in Reverberant Environment 105 6.4 Summary 106 Chapter 7 Conclusions 109 Bibliography 113 국문초록 121Docto

Multimedia Forensic Analysis via Intrinsic and Extrinsic Fingerprints

Digital imaging has experienced tremendous growth in recent decades, and digital images have been used in a growing number of applications. With such increasing popularity of imaging devices and the availability of low-cost image editing software, the integrity of image content can no longer be taken for granted. A number of forensic and provenance questions often arise, including how an image was generated; from where an image was from; what has been done on the image since its creation, by whom, when and how. This thesis presents two different sets of techniques to address the problem via intrinsic and extrinsic fingerprints. The first part of this thesis introduces a new methodology based on intrinsic fingerprints for forensic analysis of digital images. The proposed method is motivated by the observation that many processing operations, both inside and outside acquisition devices, leave distinct intrinsic traces on the final output data. We present methods to identify these intrinsic fingerprints via component forensic analysis, and demonstrate that these traces can serve as useful features for such forensic applications as to build a robust device identifier and to identify potential technology infringement or licensing. Building upon component forensics, we develop a general authentication and provenance framework to reconstruct the processing history of digital images. We model post-device processing as a manipulation filter and estimate its coefficients using a linear time invariant approximation. Absence of in-device fingerprints, presence of new post-device fingerprints, or any inconsistencies in the estimated fingerprints across different regions of the test image all suggest that the image is not a direct device output and has possibly undergone some kind of processing, such as content tampering or steganographic embedding, after device capture. While component forensics is widely applicable in a number of scenarios, it has performance limitations. To understand the fundamental limits of component forensics, we develop a new theoretical framework based on estimation and pattern classification theories, and define formal notions of forensic identifiability and classifiability of components. We show that the proposed framework provides a solid foundation to study information forensics and helps design optimal input patterns to improve parameter estimation accuracy via semi non-intrusive forensics. The final part of the thesis investigates a complementing extrinsic approach via image hashing that can be used for content-based image authentication and other media security applications. We show that the proposed hashing algorithm is robust to common signal processing operations and present a systematic evaluation of the security of image hash against estimation and forgery attacks

Multimedia Forensics

This book is open access. Media forensics has never been more relevant to societal life. Not only media content represents an ever-increasing share of the data traveling on the net and the preferred communications means for most users, it has also become integral part of most innovative applications in the digital information ecosystem that serves various sectors of society, from the entertainment, to journalism, to politics. Undoubtedly, the advances in deep learning and computational imaging contributed significantly to this outcome. The underlying technologies that drive this trend, however, also pose a profound challenge in establishing trust in what we see, hear, and read, and make media content the preferred target of malicious attacks. In this new threat landscape powered by innovative imaging technologies and sophisticated tools, based on autoencoders and generative adversarial networks, this book fills an important gap. It presents a comprehensive review of state-of-the-art forensics capabilities that relate to media attribution, integrity and authenticity verification, and counter forensics. Its content is developed to provide practitioners, researchers, photo and video enthusiasts, and students a holistic view of the field

Multimedia Forensics

This book is open access. Media forensics has never been more relevant to societal life. Not only media content represents an ever-increasing share of the data traveling on the net and the preferred communications means for most users, it has also become integral part of most innovative applications in the digital information ecosystem that serves various sectors of society, from the entertainment, to journalism, to politics. Undoubtedly, the advances in deep learning and computational imaging contributed significantly to this outcome. The underlying technologies that drive this trend, however, also pose a profound challenge in establishing trust in what we see, hear, and read, and make media content the preferred target of malicious attacks. In this new threat landscape powered by innovative imaging technologies and sophisticated tools, based on autoencoders and generative adversarial networks, this book fills an important gap. It presents a comprehensive review of state-of-the-art forensics capabilities that relate to media attribution, integrity and authenticity verification, and counter forensics. Its content is developed to provide practitioners, researchers, photo and video enthusiasts, and students a holistic view of the field

Intelligent Circuits and Systems

ICICS-2020 is the third conference initiated by the School of Electronics and Electrical Engineering at Lovely Professional University that explored recent innovations of researchers working for the development of smart and green technologies in the fields of Energy, Electronics, Communications, Computers, and Control. ICICS provides innovators to identify new opportunities for the social and economic benefits of society.　 This conference bridges the gap between academics and R&D institutions, social visionaries, and experts from all strata of society to present their ongoing research activities and foster research relations between them. It provides opportunities for the exchange of new ideas, applications, and experiences in the field of smart technologies and finding global partners for future collaboration. The ICICS-2020 was conducted in two broad categories, Intelligent Circuits & Intelligent Systems and Emerging Technologies in Electrical Engineering

Entropy in Image Analysis II

Image analysis is a fundamental task for any application where extracting information from images is required. The analysis requires highly sophisticated numerical and analytical methods, particularly for those applications in medicine, security, and other fields where the results of the processing consist of data of vital importance. This fact is evident from all the articles composing the Special Issue "Entropy in Image Analysis II", in which the authors used widely tested methods to verify their results. In the process of reading the present volume, the reader will appreciate the richness of their methods and applications, in particular for medical imaging and image security, and a remarkable cross-fertilization among the proposed research areas