33784783
A New LUT Watermarking Scheme with Near Minimum Distortion Based on the Statistical Modeling in the Wavelet Domain
This paper presents a new wavelet domain look-up table (LUT) watermarking algorithm that leads to the sub-optimal embedding of watermarks in the sense of minimizing distortion. The algorithm provides a joint distortion-robustness design of the LUT based watermark. There are two key features in the algorithm: (1) a near minimum-distortion LUT with the maximum run of 2 is designed based on the statistical properties of the wavelet coefficients; (2) an expectation-maximization (EM) algorithm based method is employed to model the statistical distribution of wavelet coefficients and select significant coefficients (coefficients with large magnitude) for watermark embedding. The experimental results show that images watermarked by the proposed algorithm have about 1.5-2.5dB peak-signal-to-noise-ratio (PSNR) gain over the conventional odd-even embedding method, while the system presents great robustness. In the case of 0.2bpp (1/40) JPEG2000 compression, the proposed scheme can ensure a reasonably low bit error rate (BER).
1661896
Multiscale Fragile Watermarking Based on the Gaussian Mixture Model
In this paper, a new multiscale fragile watermarking scheme based on the Gaussian mixture model (GMM) is presented. First, a GMM is developed to describe the statistical characteristics of images in the wavelet domain and an expectation-maximization algorithm is employed to identify GMM model parameters. With wavelet multiscale subspaces being divided into watermarking blocks, the GMM model parameters of different watermarking blocks are adjusted to form certain relationships, which are employed for the presented new fragile watermarking scheme for authentication. An optimal watermark embedding method is developed to achieve minimum watermarking distortion. A secret embedding key is designed to securely embed the fragile watermarks so that the new method is robust to counterfeiting, even when the malicious attackers are fully aware of the watermark embedding algorithm. It is shown that the presented new method can securely embed a message bit stream, such as personal signatures or copyright logos, into a host image as fragile watermarks. Compared with conventional fragile watermark techniques, this new statistical model based method modifies only a small amount of image data such that the distortion on the host image is imperceptible. Meanwhile, with the embedded message bits spreading over the entire image area through the statistical model, the new method can detect and localize image tampering. Besides, the new multiscale implementation of fragile watermarks based on the presented method can help distinguish some normal image operations such as JPEG compression from malicious image attacks and, thus, can be used for semi-fragile watermarking
1464666
Feedforward neural networks with multilevel hidden neurons for remotely sensed image classification
Artificial neural network has been, used as a powerful tool for pattern classification. However, it is difficult to train when the data exhibit non-sparse or overlapping pattern classes which is often the case in practical applications. In this paper, we introduce the feedforward neural network with the hidden layer consisting of multilevel neurons. The convergence property of one-layer neural network with multilevel neurons is proved. The new feedforward model is inherently capable of fuzzy pattern classification of non-sparse or overlapping pattern classes. As an application, we apply the network for the classification of LANDSAT TM data. The results show that this approach produces better results compared with conventional neural networks.
5695951
Video Event Detection using ICA Mixture Hidden Markov Models
In this paper, a framework that combines feature extraction, model learning, and likelihood computation, is presented for video event detection. First, the independent component analysis (ICA) is applied to the raw feature space to extract the spatial features. Then, a framework based on ICA mixture hidden Markov models (ICAMHMM) is used to exploit the spatial and temporal characteristics of the training data. After the model is learnt, the likelihood for a given video sequence is computed and then used to classify the video into a semantic event. Golf video sequences are used for simulations. The results show that the proposed method can effectively detect semantic video events.
5541899
Automatic identification of digital video based on shot-level sequence matching
To locate a video clip in large collections is very important for retrieval applications, especially for digital rights management. In this paper, we present a novel technique for automatic identification of digital video. This new algorithm is based on dynamic programming that fully uses the temporal dimension to measure the similarity between two video sequences. A normalized chromaticity histogram is used as a feature which is illumination-invariant. Dynamic programming is applied on shot-level to find the optimal nonlinear mapping between video sequences. Two new normalized distance measures are presented for video sequence matching. One measure is based on the normalization of the optimal path found by dynamic programming. The other measure combines both the visual features and the temporal information. Experimental results show that the shot-level approach is robust to frame rate conversion, color correction, and compressions. The proposed distance measures are suitable for variable-length comparisons.
44391380
Bi-directional gradient labeling and registration for gray-scale image segmentation
Watershed is one of the commonly used methods for image segmentation. In this paper, we introduce a new segmentation scheme based on bi-directional labeling and registration and prove that its segmentation performance is equivalent to that of conventional watershed but it is much more computational efficient The bi-directional labeling and registration scheme, which will be referred to as BIDS, involves only linear scans of image pixels. It uses one dimensional operations instead of queues while traditional segmentation algorithms are two dimensional problems. BIDS also provides unique labels for each homogeneous regions. In addition to achieving the same segmentation results as conventional watershed, BIDS is four times less computationally complex than the conventional watersheds by immersion.
41716369
Learning Object Models, Languages, Authoring Tools and Registry Service for Achieving Dynamic and Collaborative E-Learning
10570847
CLOCK-Pro: An Effective Improvement of the CLOCK Replacement
With the ever-growing performance gap between memory systems and disks, and rapidly improving CPU performance, virtual memory (VM) management becomes increasingly important for overall system performance. However, one of its critical components, the page replacement policy, is still dominated by CLOCK, a replacement policy developed almost 40 years ago. While pure LRU has an unaffordable cost in VM, CLOCK simulates the LRU replacement algorithm with a low cost acceptable in VM management. Over the last three decades, the inability of LRU as well as CLOCK to handle weak locality accesses has become increasingly serious, and an effective fix becomes increasingly desirable. 
 
Inspired by our I/O buffer cache replacement algorithm, LIRS [13], we propose an improved CLOCK replacement policy, called CLOCK-Pro. By additionally keeping track of a limited number of replaced pages, CLOCK-Pro works in a similar fashion as CLOCK with a VM-affordable cost. Furthermore, it brings all the much-needed performance advantages from LIRS into CLOCK. Measurements from an implementation of CLOCK-Pro in Linux Kernel 2.4.21 show that the execution times of some commonly used programs can be reduced by up to 47%.
6947307
Design of IIR orthogonal wavelet filter banks using lifting scheme
The lifting scheme is well known to be an efficient tool for constructing second generation wavelets and is often used to design a class of biorthogonal wavelet filter banks. For its efficiency, the lifting implementation has been adopted in the international standard JPEG2000. It is known that the orthogonality of wavelets is an important property for many applications. This paper presents how to implement a class of infinite-impulse-response (IIR) orthogonal wavelet filter banks by using the lifting scheme with two lifting steps. It is shown that a class of IIR orthogonal wavelet filter banks can be realized by using allpass filters in the lifting steps. Then, the design of the proposed IIR orthogonal wavelet filter banks is discussed. The designed IIR orthogonal wavelet filter banks have approximately linear phase responses. Finally, the proposed IIR orthogonal wavelet filter banks are applied to the image compression, and then the coding performance of the proposed IIR filter banks is evaluated and compared with the conventional wavelet transforms
14511182
Does internet media traffic really follow Zipf-like distribution?
It is commonly agreed that Web traffic follows the Zipf-like distribution, which is an analytical foundation for improving Web access performance by client-server based proxy caching systems on the Internet. However, some recent studies have observed non-Zipf-like distributions of Internet media traffic in different content delivery systems. Due to the variety of media delivery systems and the diversity of media content, existing studies on media traffic are largely workload specific, and the observed access patterns are often different from or even conflict with each other. For Web media systems, study [3] reports that the access pattern of streaming media is Zipf-like in a university campus network, while study [2] finds that it is not Zipf-like in an enterprise media server. For VoD media systems, study [1] finds that it is not Zipf-like in a multicast-based Media-on-Demand server of a campus network, while study [9] reports it is Zipf-like in a large VoD streaming system of an ISP. For P2P media systems, study [4] reports that the access pattern of media workload in KaZaa system collected in a campus network is not Zipf-like, while study [5] reports that it is Zipf-like in another campus network. For live streaming media systems, study [8] reports it is Zipf-like while study [6] reports it is not Zipf-like. A number of models have been proposed to explain the observed media access patterns, such as the generalized Zipf-like model [7], “fetch-at-most-once” model [4], and two-mode Zipf model [6]. However, each of these models can only explain a very limited scope of measurement results. A general model of Internet media access patterns is highly desirable for traffic engineering on the Internet and is critical to design, benchmark, and evaluate Internet media delivery systems. In this study, we have analyzed a wide variety of media workloads on the Internet. The workloads were collected from both the client side and the server side in Web, VoD, P2P, and live streaming environments between 1998 and 2006, where the media content is delivered via Web/P2P downloading or unicast/multicast streaming. The duration of these workloads ranges from a few days to more than two years and the user population ranges from several thousands to more than one hundred thousand. The number of client requests
206955905
Design of symmetric orthonormal wavelet filters using a single complex allpass filter
This paper gives a new class of real-valued symmetric orthonormal wavelet filters by using a single complex allpass filter. Firstly, the conditions that the complex allpass filter has to satisfy are derived from the symmetric and orthonormal conditions of wavelets. Then, from the viewpoint of the wavelet regularity, a new method is proposed for designing the proposed symmetric orthonormal wavelet filters with maximal flatness. In the proposed method, the maximally flat solutions can be easily obtained by solving a set of linear equations only.