18025379
Error concealment for JPEG2000 images based on orthogonal edge directed filters
We propose an error concealment algorithm for JPEG2000 image transmissions over unreliable channels. Firstly, the local principal edge information in the damaged area is detected in the spatial domain. Then the proposed orthogonal edge directed filters (OEDFs) are applied to remove the ring or ripple artifact errors due to the loss of some wavelet transform (WT) bitplane data. Two kinds of constraints in WT domain are used for rectifying the recovered WT coefficients obtained from OEDFs, namely the WT known-value constraint and the empirical statistical constraint of the WT coefficients. Finally, this filtering-and-rectifying procedure is iterated until convergent. Simulation results have shown that both objective and subjective image quality have been improved by our proposed algorithm.
11249256
A unified framework for resolving ambiguity in copy detection
Copy detection is an important component of digital rights management and can be implemented using a retrieval-based approach. Under this approach, a query image, suspected to be a copy, is compared against all the images in the owner database. The comparison is done based on a distance metric in feature space. The performance of such a system depends on the mutual separation of the feature representation of the images in the database. In this paper we propose a framework that increases this mutual separation by literally shifting them away from each other. The idea of modifying the features derives its inspiration from the field of watermarking. It is also important to make sure that the semantics of the images do not change after modification. Thus the focus of this paper is on how to modify the images in the database, so that the mutual separation between the images in feature space is above a certain threshold and the distortion induced is minimized. This problem can be formulated as a non-convex optimization problem which is difficult to solve. We propose a restriction of the problem and solve it using second-order cone programming. We present a practical implementation of our framework, named RAM, which uses AFMT as the feature representation. We conduct experiments to test the performance of RAM.
2005681
Hiding Secret Points Amidst Chaff
Motivated by the representation of biometric and multimedia objects, we consider the problem of hiding noisy point-sets using a secure sketch. A point-set X consists of s points from a d-dimensional discrete domain [0,N – 1]d. Under permissible noises, for every point $\left \langle x_1,..,x_d\right \rangle \in X$, each xi may be perturbed by a value of at most δ. In addition, at most t points in X may be replaced by other points in [0,N – 1]d. Given an original X, we want to compute a secure sketch P. A known method constructs the sketch by adding a set of random points R, and the description of (X∪R) serves as part of the sketch. However, the dependencies among the random points are difficult to analyze, and there is no known non-trivial bound on the entropy loss. In this paper, we first give a general method to generate R and show that the entropy loss of (X∪R) is at most s(dlogΔ+ d + 0.443), where Δ= 2δ+1. We next give improved schemes for d = 1, and special cases for d = 2. Such improvements are achieved by pre-rounding, and careful partition of the domains into cells. It is possible to make our sketch short, and avoid using randomness during construction. We also give a method in d = 1 to demonstrate that, using the size of R as the security measure would be misleading.
6661888
A wavelet approach to foveating images
Motivated by applications of foveated images in visualization, we introduce the foveation transform of an image. We study the basic properties of these transforms using the multiresolution framework of Mallat. We also consider practical methods of realizing such transforms. In particular, we introduce a new method for foveating images based on wavelets. Preliminary experimental results are shown.
472683
On the effectiveness of DDoS attacks on statistical filtering
Distributed denial of service (DDoS) attacks pose a serious threat to service availability of the victim network by severely degrading its performance. Recently, there has been significant interest in the use of statistical-based filtering to defend against and mitigate the effect of DDoS attacks. Under this approach, packet statistics are monitored to classify normal and abnormal behaviour. Under attack, packets that are classified as abnormal are dropped by the filter that guards the victim network. We study the effectiveness of DDoS attacks on such statistical-based filtering in a general context where the attackers are "smart". We first give an optimal policy for the filter when the statistical behaviours of both the attackers and the filter are static. We next consider cases where both the attacker and the filter can dynamically change their behaviour, possibly depending on the perceived behaviour of the other party. We observe that while an adaptive filter can effectively defend against a static attacker, the filter can perform much worse if the attacker is more dynamic than perceived.
42674644
Shortest Path amidst Disc Obstacles Is Computable
An open question in Exact Geometric Computation is whether there are transcendental computations that can be made "geometrically exact". Perhaps the simplest such problem in computational geometry is that of computing the shortest obstacle-avoiding path between two points p,q in the plane, where the obstacles are a collection of n discs. This problem can be solved in O(n2log n) time in the Real RAM model, but nothing was known about its computability in the standard (Turing) model of computation. We first give a direct proof of the Turing-computability of this problem, provided the radii of the discs are rationally related. We make the usual assumption that the numerical input data are real algebraic numbers. By appealing to effective bounds from transcendental number theory, we further show a single-exponential time upper bound when the input numbers are rational. Our result appears to be the first example of a non-algebraic combinatorial problem which is shown computable. It is also a rare example of transcendental number theory yielding positive computational results.
18150673
The anatomy of a multimodal information filter
The proliferation of objectionable information on the Internet has reached a level of serious concern. To empower end-users with the choice of blocking undesirable and offensive websites, we propose a multimodal information filter, named MORF. In this paper, we present MORF's core components: its confidence-based classifier, a Cross-bagging ensemble scheme, and multimodal classification algorithm. Empirical studies and initial statistics collected from the MORF filters deployed at sites in the U.S. and Asia show that MORF is both efficient and effective, due to our classification methods.
7526155
BubbleUp: low latency fast-scan for media servers
Interactive multimedia applications require fast response time. Traditional disk scheduling schemes can incur high latencies, and caching data in memory to reduce latency is usually not feasible, especially if fast-scans need to be supported. In this study we propose a disk-based solution called BubbleUp. It significantly reduces the initial latency for new requests, as well as for fast-scan requests. The throughput of the scheme is comparable to that of traditional schemes, and it may even provide better throughput than mechanisms based on elevator disk scheduling. BubbleUp incurs a slight disk storage overhead, but we argue that through effective allocation, this cost can be minimized.
6693066
Nnew: nearest neighbor expansion by weighting in image database retrieval
Various systems have been developed for supporting content-based image retrieval. Most systems make very strong assumptions in modeling users’ query concepts. However, since the information need of users can be very diverse, these assumptions may not always hold and hence can lead to poor search results. For instance, if a system assumes that the query-concept is convex but a user issues a disjunctive query, and vice versa, the search result cannot be satisfactory. In this study, we propose a method that can approximate more complex (non-convex and disjunctive) query concepts. Our method uses intelligent modeling and learning to increase query speed and accuracy. Empirical results show that our method converges consistently faster than some traditional approaches on different datasets.
11046380
Reducing Initial Latency in Media Servers
A multimedia server needs to provide high bandwidth and continuous real-time delivery. We present techniques for reducing the initial latency of presentations. This is important in interactive applications such as video games and multimedia document browsing. On-disk partial data replication can significantly reduce initial latency without adversely affecting throughput.
46114840
An Architecture of a Web-Based Collaborative Image Search Engine
We present a perception-based paradigm for image retrieval. The central component of this paradigm is a query-concept learner, which can learn users' subjective query concepts through an intelligent sampling process. We show that the learner can collect user feedback and use it to perform collaborative image annotation in addition to learning subjective query concepts. On the one hand, the improved annotation can help provide better initial keyword-search results to seed perception-based image retrieval. On the other hand, the more effective image-research results can further refine annotation quality. The users of the system collaboratively help improve search quality through the query-concept learner. Our empirical results show that an image retrieval system powered by this perception-based paradigm performs significantly better than traditional systems in search accuracy, in multimodal integration, and in capability for personalization.