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Security issues are important concerns of image hashing. A type of image hashing needs to randomly divide a given image into several parts, usually rectangles. However, the security problem arises due to the rectangular shapes. So, we propose a new method which enhances the randomness by dividing the image into zigzag blocks with random walk. Security analyses are provided, and experiments show our...
Steganography assumes extremely significant part in the field of data covering up for mystery correspondence. It is a secret correspondence to conceal mystery information in spread media (e.g. content, sound, video, picture and so on). Steganography works in Spatial and Transform domain. Spatial domain achieves better capacity but low robustness while Transform domain achieves robustness along with...
Feature selection is an effective technique for dimensionality reduction to get the most useful information from huge raw data. Many spectral feature selection algorithms have been proposed to address the unsupervised feature selection problem, but most of them fail to pay attention to the noises induced during the feature selection process. In this paper, we not only consider the feature structural...
Regional monitoring of land cover conversion of natural vegetation to new informal human settlements is essential when investigating the migration of people to urbanized cities. Detecting these new settlements require reliable change detection methods. A robust change detection metric can be derived by analyzing the area under the autocorrelation function for a time series. The time dependence on...
Infographic is a type of information visualization that uses graphic design to enhance human ability to identify patterns and trends. It is popularly used to support spread of information. Yet, there are few studies that investigate how infographics affect learning and how individual factors, such as learning styles and enjoyment of the information affect infographics perception. In this sense, this...
Robust optimization has gained increasing attention in the power system area due to its ability to model uncertainties using modest information while producing reliable solutions. However, a common concern with the robust approach is that it can be overly-conservative. To address this issue, we propose a data-driven method to construct uncertainty sets by using autoregressive integrated moving average...
In this paper, we propose a robust visual tracking method based on a temporal ensemble framework. Different from conventional ensemble-based trackers, which combine weak classifiers into a strong one using AdBoost in spatial fusion manners, our method adopts a powerful and efficient tracker integrated with its snapshots in different temporal windows of online tracking process to construct a temporal...
In web topic detection, detecting “hot” topics from enormous User-Generated Content (UGC) on web data poses two main difficulties that conventional approaches can barely handle: 1) poor feature representations from noisy images and short texts; and 2) uncertain roles of modalities where visual content is either highly or weakly relevant to textual cues due to less-constrained data. In this paper,...
Object tracking is a challenging topic in the field of computer vision since its performance is easily disturbed by occlusion, illumination change, background clutter, scale variation, etc. In this paper, we introduce a robust tracking algorithm that fuses information from both visible images and infrared (IR) images. The proposed tracking algorithm not only incorporates convolutional feature maps...
In echo-based audio watermarking methods, poor robustness and low embedding capacity are the main problems. In this paper, we propose a novel time-spread echo method for audio watermarking, aiming to improve the robustness and the embedding capacity. To improve the robustness, we design an efficient pseudonoise (PN) sequence and a corresponding decoding function. Compared to the conventional PN sequence...
This paper explores the viability of Hartley Transforms as an alternative to Fourier Transforms for Face Recognition. The paper provides a brief introduction to Hartley Transform, which is a reasonable alternate to Fourier Transform due to its similarities in the choice of basis function. Correlation filter is a pattern recognition tool that is efficient and robust. This includes extraction of features...
This paper deals with key performance indicator (KPI) related fault detection system design issues based on an integrated framework. The characteristics of the projection directions and the extracted subspaces are discussed in details. In comparison with the basic PLS based approach, the proposed algorithm improves the decomposition performance with respect to KPI. In the meantime, by incorporating...
Watermarking, known as a typical active network traffic analysis technique, has been widely used in stepping stone detecting and anonymity tracing. Among several different watermarking schemes, the interval centroid based watermarking scheme has shown its robustness in the problems such as chaff packet, packet drops and repacketization. It can be widely used in many applications, for it embeds watermarking...
In this paper, we study the long-term cooperative tracking in large areas using multiple unmanned aerial vehicles (UAVs). Firstly, a hybrid tracking algorithm, which switches between a correlation filters based tracker and a cascaded detector, is developed for the robust long-term tracking using a single UAV. Then, a centralized cooperation strategy is proposed to achieve cooperative tracking using...
In many applications of image watermarking, its real-time implementation is required. Although Hardware implementation is regarded as a proper types of real-time implementation; most algorithms are too complex for hardware implementation. In this paper an adaptive watermarking and its improved is presented which uses bit-plane congestion to achieve transparency and robustness. A congestion analysis...
Medical Image Watermarking has been proposed as a solution to deal with the problems of integrity, authenticity, and confidentiality and communications secrecy of medical images over networked environments. Medical image watermarking schemes exploit crucial traits of the medical image but this is not so for conventional images. In this paper, we compare the performance of block based SVD watermarking...
Compressed sensing, further to its ability of reducing resources spent in signal acquisition, may be seen as an implicit private-key encryption scheme. The level of achievable secrecy has been analyzed in the most classical settings, when the sensing matrix is made of independent and identically distributed entries. Yet, it is known that substantially improved acquisition can be achieved by tuning...
Functional Magnetic Resonance Imaging (fMRI) methods produce high dimensional representation of cognitive processes under heavy noise due to the limitations of hardware and measurement techniques. In order to reduce the noise and extract useful information from the fMRI data, a sequence of pre-processing techniques, such as smoothing with spatial filters and z-scoring, are used. In this study, we...
In this paper, we present a linear method that incorporates information from neighboring pixels for sub-pixel matching. Two algorithms are presented. Both rely on a rough initial estimate of the disparity. The first one is optimized for pairs of images requiring negligible window deformation. The second method is slower but more general and more precise. It is applicable for large window deformation...
Watermarking is a technology that complements cryptography by embedding imperceptible signals in work. Information hiding techniques have recently become important in a number of application areas. Digital audio, video and images are increasingly furnished with distinguishing but imperceptible marks, which may contain a hidden copyright notice that helps to prevent unauthorized copying directly. One...
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