Sharif Digital Repository

Steganalysis is the science of detecting covert communication. It is called blind (universal) if designed to detect stego images steganographied by a wide range of embedding methods. In this method, statistical properties of the image are explored, regardless the embedding procedure employed. The main problem for image steganalysis is to find sensitive features and characteristics of the image which make a statistically significant difference between the clean and stego images. In this thesis we propose a blind image steganalysis method based on the singular value decomposition (SVD) of the discrete cosine transform (DCT) coefficients that are revisited in this work in order to enhance the... 

The rapid increase in the size of digital multimedia data collections has resulted in wide availability of multimedia contents to the general users. Effective and efficient management of these collections is an important task that has become a focus in the research of multimedia signal processing and pattern recognition. In this thesis, we address the problem of automatic classification of music, as one of the main multimedia signals. In this context, music genres are crucial descriptors that are widely used to organize the large music collections. The two main components of automatic music genre classification systems are feature extraction and classification. While features are a compact... 

This project aims at forgery detection in digital videos. Most of existing methods are based on similar methods for image forgery detection. Therefore, they do not have sufficient accuracy in case of video forgery detection. In this project, we focus on local copy/move attacks in digital videos and propose 3 solutions for 3 problems in this field: 1) detection of copy/move along time axis (temporal copy/move), 2) detection of copy/move along x and y axes (spatial copy/move) and 3) detection of original and fake part in case of finding a duplication. For each of these 3 problems a feature extraction algorithm and a forgery detection algorithm are proposed. Feature extraction algorithms are... 

This thesis explored and described a new steganalysis system modeling. Image steganalysis systems are divided into two parts: feature extraction from images and classification of images. Many researches have been done in both parts and satisfactory results have also been reported. There are acceptable steganalysis methods which work accurately in high rates of steganography; however steganography in low rates is still undetectable. By lowering the rate of steganography in images, the difference between stego images and clean images would be reduced which accordingly led to the reduction of the difference between the corresponding extracted features. Thus, the ability of classification... 

Data hiding in digital media has been widely investigated over the past decade because of covering different crucial applications. Amongst digital multimedia signals, video has been received a special attention and data hiding in video signals has reached a significant improvement in recent years. This thesis aims at introducing an information theoretic based analysis method for calculating the capacity of data hiding in video signals, as one of most challenging issues in this area. This analysis is expected to establish a reasonable basis for the design and analysis of data hiding algorithms. We study and investigate the data hiding problems that could be specific to video signals and its... 

Blind image steganalysis is a technique used to, which require no prior information about the steganographic method applied to the stego im- age, determine whether the image contains an embedded message or not. The basic idea of blind steganalysis is to extract some features sensitive to information hiding, and then exploit classifiers for judging whether a given test image contains a secret message.The main focus of this research is to design an choose features sen-sitive to the embedding changes. In fact, we use high order moments in different domains, such as spatial, DCT and multi-resolution do-main, in order to improve the performance of existing steganalyzers.Accordingly, First, we... 

Owing to the unprecedented increasing rate of introducing new means of editing and transferring videos, appropriate and efficient methods for authentication and tampering detection are already playing a pivotal role in today's world. Amongst various methods for authentication, tampering detection and property right protection, the focus of this thesis is on watermarking. In the first place, we will present watermarking methods based upon H.264 standard. Due to the fact that almost all of the video products are stored and distributed in compressed file formats, the ability to retrieve the watermark after video compression is of crucial importance. Hence watermarking whilst video compression... 

Availability of video recording instruments and ease of working with video editing tools have made contents of this digital signal unreliable in general. The goal of this thesis is to present a method to detect tampering of compressed videos in H.264/AVC format and restoring an approximate version of its original contents using watermarking. In the proposed scheme, a low resolution image from a number of video frames in certain time slots are embedded into the DCT coefficients of the other parts of the video which are adequately far from the reference frames. For detecting temporal and spatial tampering, the index of each frame and macroblock is embedded into itself as an authentication... 

Recognition of complex visual events has attracted much interest in recent years. Compared to somehow similar tasks like action recognition, event recognition is much more complex, primarily because of huge intra-class variation of events, variable video durations, lack of pre-imposed video structures, and severe preprocessing noises. To deal with these complexities and improve the state of the art approaches to the problem of video understanding, this thesis is focused on video event recognition based on frame level CNN descriptors. Using transfer learning, the image trained descriptors are applied to the video domain to make event recognition feasible in scenarios with limited... 

In this project we proposed a new method for improving the detection abality of a steganalyser with a pre-processing on contents of an image. Steganalysis, using machine learning, is designing a classifier with two classes: Stego or Cover. This classifier should be trained with extracted features from signal. The result of the training procedure is a machine that decides a signal belongs to stego or cover class. The first step of steganalysis process is extraction of proper features from signal. Proper feature is a variable that represents all of the useful properties of signal. Second step of this process is classifying data to two class of stego and cover. Many algorithms are proposed for... 

Recent developments of internet technology and digital media have led to the rapid growth of the steganography systems. Steganography is the art and science of concealing a secret message in a cover without leaving a perceptible or detectable trace of the message. Therefore, steganography methods, capable of embedding the largest possible amount of data with least distortion to the cover media, are highly demanding. The LSB steganography is a primary and simple method with high embedding capacity, where higher robustness is achieved if it is applied to the cover signal in the transform domain. However, regardless of the embedding domain, an essential robustness issue with the LSB... 

Steganography is the art and science of writing hidden messages in such a way that no one, apart from the sender and intended recipient, suspects the existence of the message, a form of security through obscurity. In this thesis, we focus on entropic issue of multimedia signal in the two branches of Information hiding namely Steganography and Watermarking. How to choose the block and noise estimation in the watermarking, and analysis of the singular values decomposition in steganography are examples of using entopic issue which we use in our thesis. The two new designs for video signals AVI are presented in Watermarking. For the both proposed method ,first AVI video signal will be divided... 

Nowadays, steganography is one of the secure communication methods. Exploitation of modern technologies has increased transmission bandwidth to a considerable scale. As a result of this, the multimedia signals such as Audio and Image have been used in communications widely. This application has led to the prevalent use of these signals as cover signals for carrying hidden messages. Given the proliferation of digital images, especially on the Internet, and given the large amount of redundant bits present in the digital representation of an image, images are the most popular cover objects for steganography. Simultaneously, steganalysis tries to defeat the very purpose of steganography by... 

Image steganalysis is the technique and art of detecting covert communication via images.Reduction of features dimentionality is an important issue according to accuracy and time complexity. In this thesis, GA (genetic algorithm) and PSO (Particle Swarm Optimization) are used to reduce the dimentionality of JRM, a recently proposed feature set containing 11255 features which looks high dimentional compared to other feature sets which has been reduced by evolutionary algorithms so far. So, inspite of other works done using evolutionary algorithms in this field, we use the class sepearability criterion as fitness function instead of the accuracy of the classifier. Investigating these features,... 

The purpose of this project is to improve current speaker verification techniques with short utterance using phonetic information extraction. I-vector technique is widely used in speaker verification systems. Different speakers span a subspace of universal acoustic space, which is usually modeled by “Universal Background model”. Speaker-specific subspace depends on the voice of speaker. In state-of-the-art speaker verification systems i-vectors are extracted by a factor analysis technique to represent speaker characteristics. Studies demonstrate that voiced phonemes contain more speaker-specific information than unvoiced. In this thesis we have classified voiced frames in order to exploit... 

Today, with the increasing proliferation of digital tools, manipulating digital images has become a simple matter. Therefore, in many cases related to Forensics, issues related to the intellectual property, we need to verify the authenticity of the images. There are different types of image manipulation, but image splicing manipulation is the most frequent among the types of manipulations due to its simplicity and availability.In many applications, in addition to detection, the localization of the manipulated part, which is considered segmentation at the pixel level, is also of great importance.In this project, by using a structure based on deep encoder networks, a method for improving the... 

Nowadays, using of digital cameras is streaming across the world dramatically. Application of these devices is very diverse. One of the most interesting application of those is face verification. For example, imagine your smartphone has an application which verifies faces in front of its front camera, if that face be your face (with variation from original) then application automatically unlocks your phone. Face verification systems are also deployed in airports to verify passport photos and in smart homes. One of the most regular problems in face verification is occlusion. When your face is occluded with natural or random changes we can say your face is occluded. All of the recent papers... 

Steganalysis is the process of discovering existence of hidden data in a file or image. Recent advances in steganographic methods result in their wide use in secure communications applications. Reports of using information hiding by criminals to send messages, and malwares to communicate to servers, emphasizes importance of steganalysis in real time applications. Due to wide use of JPEG images in social media and internet, steganalysis of JPEG images is a highly active research topic in information hiding. Number of steganographic tools available for steganography in JPEG domain, shows importance of steganalysis of this image format. Classic Steganalysis techniques combine feature... 

Deep neural networks have not progresses comparative until last decade due to computational complexity and principal challenges as gradient vanishing. Thanks to newly designed hardware architecture and great breakthroughs in 2000s leading to the solution of principal challenges, we currently face a tsunami of deep architecture utilization in various machine learning applications. Sparsity of a representation as a feature to make it more descriptive has been considered in different deep learning architectures leading to different formulations where sparsity is impose on specific representations. Due to the gradient based optimization methods for training deep architecture, smooth regularizers... 

Speech is the most natural and widely used approach to communication between people and the fastest communication between humans and computers. Advances have been made in this area to achieve complete success in the natural human-computer relationship. The big challenge in this way is the inability of the computer to recognize the user's feelings; Therefore, in speech processing, one of the things that should be studied and considered is; detection of emotion from a speech by a computer. This is because Emotion recognition of speech can help extract meanings and improve the functioning of the speech recognition system. This study first defined the emotions and materials needed to build...