283 research outputs found

    QUALITY-DRIVEN CROSS LAYER DESIGN FOR MULTIMEDIA SECURITY OVER RESOURCE CONSTRAINED WIRELESS SENSOR NETWORKS

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    The strong need for security guarantee, e.g., integrity and authenticity, as well as privacy and confidentiality in wireless multimedia services has driven the development of an emerging research area in low cost Wireless Multimedia Sensor Networks (WMSNs). Unfortunately, those conventional encryption and authentication techniques cannot be applied directly to WMSNs due to inborn challenges such as extremely limited energy, computing and bandwidth resources. This dissertation provides a quality-driven security design and resource allocation framework for WMSNs. The contribution of this dissertation bridges the inter-disciplinary research gap between high layer multimedia signal processing and low layer computer networking. It formulates the generic problem of quality-driven multimedia resource allocation in WMSNs and proposes a cross layer solution. The fundamental methodologies of multimedia selective encryption and stream authentication, and their application to digital image or video compression standards are presented. New multimedia selective encryption and stream authentication schemes are proposed at application layer, which significantly reduces encryption/authentication complexity. In addition, network resource allocation methodologies at low layers are extensively studied. An unequal error protection-based network resource allocation scheme is proposed to achieve the best effort media quality with integrity and energy efficiency guarantee. Performance evaluation results show that this cross layer framework achieves considerable energy-quality-security gain by jointly designing multimedia selective encryption/multimedia stream authentication and communication resource allocation

    Data Hiding and Its Applications

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    Data hiding techniques have been widely used to provide copyright protection, data integrity, covert communication, non-repudiation, and authentication, among other applications. In the context of the increased dissemination and distribution of multimedia content over the internet, data hiding methods, such as digital watermarking and steganography, are becoming increasingly relevant in providing multimedia security. The goal of this book is to focus on the improvement of data hiding algorithms and their different applications (both traditional and emerging), bringing together researchers and practitioners from different research fields, including data hiding, signal processing, cryptography, and information theory, among others

    PERFORMANCE ANALYSIS OF DIFFERENT SCHEMES FOR TRANSMISSION OF WATERMARKED MEDICAL IMAGES OVER FADING CHANNELS

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    ABSTRACT Performance Analysis of Different Schemes for Transmission of Watermarked Medical images over Fading Channels Praveen Kumar Korrai In this thesis, we investigate different types of robust schemes for transmission of medical images with concealed patient information as a watermark. In these schemes, spatial domain digital watermarking technique is adapted to embed the patient information as a watermark into the lower order bits of the medical images to reduce the storage and transmission overheads. The watermark, which comprises text data, is encrypted to prevent unauthorized access of data. To enhance the robustness of the embedded information, the encrypted watermark is coded by concatenation of Reed Solomon (RS) and low density parity check (LDPC) codes. A robust scheme for transmission of watermarked images over impulsive noisy wireless channels is first proposed and its performance analyzed. In this scheme, the bursty wireless channel is simulated by adding impulse noise to the watermark embedded image. Furthermore, turbo channel coding is used to correct the transmission errors over impulsive noisy wireless channels. However, single input single output (SISO) channel capacity is not enough to provide modern wireless services such as data and multimedia messaging services. Further, it is not reliable due to multipath fading. To overcome these problems, a multiple-input multiple-output (MIMO) transmission scheme in which multiple antennas are used at both the transmitter and the receiver has emerged as one of the most significant technical breakthroughs in modern wireless communications. MIMO can improve the channel capacity and provide diversity gain. Hence, a scheme with a MIMO channel is proposed for the transmission of watermarked medical images over Rayleigh flat fading channels and its performance analyzed using MIMO maximum likelihood detector at the receiver. We present another scheme, namely, MIMO space frequency block coded OFDM (MIMO SFBC OFDM) in this thesis for transmission of watermarked medical images over Rayleigh fading channels to mitigate the detrimental effects due to frequency selective fading. The performance of this MIMO SFBC OFDM scheme is analyzed and compared with that of SISO-OFDM using minimum mean square error V-BLAST- based detection at the receiver. The efficacy of the different proposed schemes is illustrated through implementation results on watermarked medical images

    Image watermarking, steganography, and morphological processing

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    With the fast development of computer technology, research in the fields of multimedia security, image processing, and robot vision have recently become popular. Image watermarking, steganogrphic system, morphological processing and shortest path planning are important subjects among them. In this dissertation, the fundamental techniques are reviewed first followed by the presentation of novel algorithms and theorems for these three subjects. The research on multimedia security consists of two parts, image watermarking and steganographic system. In image watermarking, several algorithms are developed to achieve different goals as shown below. In order to embed more watermarks and to minimize distortion of watermarked images, a novel watermarking technique using combinational spatial and frequency domains is presented. In order to correct rounding errors, a novel technique based on the genetic algorithm (GA) is developed. By separating medical images into Region of Interest (ROI) and non-ROI parts, higher compression rates can be achieved where the ROI is compressed by lossless compression and the non-ROI by lossy compression. The GA-based watermarking technique can also be considered as a fundamental platform for other fragile watermarking techniques. In order to simplify the selection and integrate different watermarking techniques, a novel adjusted-purpose digital watermarking is developed. In order to enlarge the capacity of robust watermarking, a novel robust high-capacity watermarking is developed. In steganographic system, a novel steganographic algorithm is developed by using GA to break the inspection of steganalytic system. In morphological processing, the GA-based techniques are developed to decompose arbitrary shapes of big binary structuring elements and arbitrary values of big grayscale structuring elements into small ones. The decomposition is suited for a parallel-pipelined architecture. The techniques can speed up the morphological processing and allow full freedom for users to design any type and any size of binary and grayscale structuring elements. In applications such as shortest path planning, a novel method is first presented to obtaining Euclidean distance transformation (EDT) in just two scans of image. The shortest path can be extracted based on distance maps by tracking minimum values. In order to record the motion path, a new chain-code representation is developed to allow forward and backward movements. By placing the smooth turning-angle constraint, it is possible to mimic realistic motions of cars. By using dynamically rotational morphology, it is not only guarantee collision-free in the shortest path, but also reduce time complexity dramatically. As soon as the distance map of a destination and collision-free codes have been established off-line, shortest paths of cars given any starting location toward the destination can be promptly obtained on-line

    Discrete Wavelet Transforms

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    The discrete wavelet transform (DWT) algorithms have a firm position in processing of signals in several areas of research and industry. As DWT provides both octave-scale frequency and spatial timing of the analyzed signal, it is constantly used to solve and treat more and more advanced problems. The present book: Discrete Wavelet Transforms: Algorithms and Applications reviews the recent progress in discrete wavelet transform algorithms and applications. The book covers a wide range of methods (e.g. lifting, shift invariance, multi-scale analysis) for constructing DWTs. The book chapters are organized into four major parts. Part I describes the progress in hardware implementations of the DWT algorithms. Applications include multitone modulation for ADSL and equalization techniques, a scalable architecture for FPGA-implementation, lifting based algorithm for VLSI implementation, comparison between DWT and FFT based OFDM and modified SPIHT codec. Part II addresses image processing algorithms such as multiresolution approach for edge detection, low bit rate image compression, low complexity implementation of CQF wavelets and compression of multi-component images. Part III focuses watermaking DWT algorithms. Finally, Part IV describes shift invariant DWTs, DC lossless property, DWT based analysis and estimation of colored noise and an application of the wavelet Galerkin method. The chapters of the present book consist of both tutorial and highly advanced material. Therefore, the book is intended to be a reference text for graduate students and researchers to obtain state-of-the-art knowledge on specific applications

    DCT-Based Image Feature Extraction and Its Application in Image Self-Recovery and Image Watermarking

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    Feature extraction is a critical element in the design of image self-recovery and watermarking algorithms and its quality can have a big influence on the performance of these processes. The objective of the work presented in this thesis is to develop an effective methodology for feature extraction in the discrete cosine transform (DCT) domain and apply it in the design of adaptive image self-recovery and image watermarking algorithms. The methodology is to use the most significant DCT coefficients that can be at any frequency range to detect and to classify gray level patterns. In this way, gray level variations with a wider range of spatial frequencies can be looked into without increasing computational complexity and the methodology is able to distinguish gray level patterns rather than the orientations of simple edges only as in many existing DCT-based methods. The proposed image self-recovery algorithm uses the developed feature extraction methodology to detect and classify blocks that contain significant gray level variations. According to the profile of each block, the critical frequency components representing the specific gray level pattern of the block are chosen for encoding. The code lengths are made variable depending on the importance of these components in defining the block’s features, which makes the encoding of critical frequency components more precise, while keeping the total length of the reference code short. The proposed image self-recovery algorithm has resulted in remarkably shorter reference codes that are only 1/5 to 3/5 of those produced by existing methods, and consequently a superior visual quality in the embedded images. As the shorter codes contain the critical image information, the proposed algorithm has also achieved above average reconstruction quality for various tampering rates. The proposed image watermarking algorithm is computationally simple and designed for the blind extraction of the watermark. The principle of the algorithm is to embed the watermark in the locations where image data alterations are the least visible. To this end, the properties of the HVS are used to identify the gray level image features of such locations. The characteristics of the frequency components representing these features are identifying by applying the DCT-based feature extraction methodology developed in this thesis. The strength with which the watermark is embedded is made adaptive to the local gray level characteristics. Simulation results have shown that the proposed watermarking algorithm results in significantly higher visual quality in the watermarked images than that of the reported methods with a difference in PSNR of about 2.7 dB, while the embedded watermark is highly robustness against JPEG compression even at low quality factors and to some other common image processes. The good performance of the proposed image self-recovery and watermarking algorithms is an indication of the effectiveness of the developed feature extraction methodology. This methodology can be applied in a wide range of applications and it is suitable for any process where the DCT data is available

    Detection of Geometric Transformations in Copy-Move Forgery of Digital Images

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    Digital Forensics is a branch of forensic science which is related to cyber crime. It basically involves the detection, recovery and investigation of material found in digital devices. Digital images and videos plays most important role in digital forensics. They are the prime evidences of any crime scene. So the fidelity of the image is important. Digital images can be easily manipulated and edited with the help of image processing tools. Copy-move Forgery is the most primitive form of cyber attack on digital images. In Copy-move forgery a part of image (region) itself is copied and pasted into another part of the same image. The intension behind this type of attack is to “add” or “disappear” some objects from the image. Hence to break the fidelity of the image and fool the viewer. Copy-move attack is more prevalent in images having uniform texture or patterns, for e.g. sand, grass, water etc. In this thesis exact block matching is used as a detection technique. This technique is based on block matching, for these the whole image is divided into number of block and then the matching process is applied. Sometimes the copied region is processed before pasted i.e. some geometric transformations is applied on the pasted region. The transformations like scaling, rotation etc. It is not possible for human eyes to detect such kind of forgeries. Whenever forgery is done in this manner the common techniques like block matching, exhaustive search, auto-correlation and robust match etc. are not able to detect the forgery having geometric transformations. So that for identification of forged region we need some technique which are based on local features and also invariant to transformations. In this thesis SIFT is used for forgery detection. SIFT stands for Scale Invariant Feature Transform, this gives local feature points which are invariant to scales. The key points helps to find the duplicated region with different matching algorithm

    Multibiometric security in wireless communication systems

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    This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University, 05/08/2010.This thesis has aimed to explore an application of Multibiometrics to secured wireless communications. The medium of study for this purpose included Wi-Fi, 3G, and WiMAX, over which simulations and experimental studies were carried out to assess the performance. In specific, restriction of access to authorized users only is provided by a technique referred to hereafter as multibiometric cryptosystem. In brief, the system is built upon a complete challenge/response methodology in order to obtain a high level of security on the basis of user identification by fingerprint and further confirmation by verification of the user through text-dependent speaker recognition. First is the enrolment phase by which the database of watermarked fingerprints with memorable texts along with the voice features, based on the same texts, is created by sending them to the server through wireless channel. Later is the verification stage at which claimed users, ones who claim are genuine, are verified against the database, and it consists of five steps. Initially faced by the identification level, one is asked to first present one’s fingerprint and a memorable word, former is watermarked into latter, in order for system to authenticate the fingerprint and verify the validity of it by retrieving the challenge for accepted user. The following three steps then involve speaker recognition including the user responding to the challenge by text-dependent voice, server authenticating the response, and finally server accepting/rejecting the user. In order to implement fingerprint watermarking, i.e. incorporating the memorable word as a watermark message into the fingerprint image, an algorithm of five steps has been developed. The first three novel steps having to do with the fingerprint image enhancement (CLAHE with 'Clip Limit', standard deviation analysis and sliding neighborhood) have been followed with further two steps for embedding, and extracting the watermark into the enhanced fingerprint image utilising Discrete Wavelet Transform (DWT). In the speaker recognition stage, the limitations of this technique in wireless communication have been addressed by sending voice feature (cepstral coefficients) instead of raw sample. This scheme is to reap the advantages of reducing the transmission time and dependency of the data on communication channel, together with no loss of packet. Finally, the obtained results have verified the claims
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