17092169
Robust anisotropic diffusion to produce enhanced statistical parametric map from noisy fMRI
This paper presents a new, simple, and elegant technique to obtain enhanced statistical parametric maps (SPMs) from noisy functional magnetic resonance imaging (fMRI) data. This technique is based on the robust anisotropic diffusion (RAD), a technique normally used as an edge-preserving filter. A direct application of the RAD to the fMRI data does not work, because in this case RAD would perform an edge-preserving filtering of the fMRI structural information, instead of enhancing its functional information. The RAD can be applied directly to SPM but, in this case, only a small improvement of the SPM quality can be achieved, because the originating fMRI is not taken into account. To overcome these difficulties, we propose to estimate the SPM from the noisy fMRI, compute the diffusion coefficients in the SPM space, and then perform the diffusion in the structural information-removed fMRI data using the coefficients previously computed. These steps are iterated until convergence. We have tested the new technique in both simulated and real fMRI images, yielding surprisingly sharp and noiseless SPMs with increased statistical significance. We also describe how to automatically estimate an appropriate scale parameter.
6422604
Image reconstruction using divergent beams distributed over limited angle
We present a new image reconstruction technique from acquisition data in divergent geometry distributed over a limited angle. In many practical situations, it is not possible to obtain the data distributed over the whole 360/spl deg/. For example, when the test object presents anisotropic properties, i.e., when it is extremely sensible to the radiation coming from some specific direction. Physical constraints can also obstruct the acquisition of data in all angles. The proposed technique solves this problem by allowing image reconstruction from data distributed over a limited angle. This technique first converts the divergent projections distributed over a limited angle into parallel projections homogeneously distributed over the whole contour of the test object. Then, an algorithm based on extended entropy reconstructs the image.
17995343
Automatic design of nonlinear filters by nearest neighbor learning
Nonlinear filters have been used not only in noise elimination but in a wide variety of image processing applications. Traditionally the design of a digital filter is a manual task and the user accomplishes it based on previous experiences. Unfortunately often this is not a trivial task. Thus some works try to overcome this difficulty constructing the filters automatically by computational learning neural networks, genetic algorithms and statistical estimation. These works use typical input-output images of the application as the training samples. Many different kinds of filters can be easily constructed using this approach. This paper proposes the use of nearest neighbor (NN) learning to automatic filter construction. The kd-tree (k-dimensional binary tree) is used to accelerate the NN searching. A texture recognition application example is depicted.
16590165
New Public-Key Authentication Watermarking for JBIG2 Resistant to Parity Attacks
An authentication watermark is a hidden data inserted into an image that allows detecting any alteration made in the image. AWTs (Authentication Watermarking Techniques) normally make use of secret- or public-key cryptographic cipher to compute the authentication signature of the image, and inserts it into the image itself. Many previous public-key AWTs for uncompressed binary images can be attacked by an image adulterating technique named “parity attack.” JBIG2 is an international standard for compressing bi-level images (both lossy and lossless). The creation of secure AWTs for compressed binary images is an important practical problem. However, it seems that no AWT for JBIG2 resistant to parity attacks has ever been proposed. This paper proposes a new data-hiding method to embed information in the text region of JBIG2 files. Then, we use this technique to design a new AWT for JBIG2-encoded images resistant to parity attacks. Both the secret- and public-key versions of the proposed AWT are completely immune against parity attacks. Moreover, watermarked images are visually pleasant, without visible salt and pepper noise. Image authenticity verification can be performed in either JBIG2 file itself or in the binary image obtained by decoding the JBIG2 file.
15149884
Inverse halftoning by decision tree learning
Inverse halftoning is the process to retrieve a (gray) continuous-tone image from a halftone. Recently, machine-learning-based inverse halftoning techniques have been proposed. Decision-tree learning has been applied with success to various machine-learning applications for quite some time. In this paper, we propose to use decision-tree learning to solve the inverse halftoning problem. This allows us to reuse a number of algorithms already developed. Especially, the maximization of entropy gain is a powerful idea that makes the learning algorithm to automatically select the ideal window as the decision-tree is constructed. The new technique has generated gray images with PSNR numbers, which are several dB above those previously reported in the literature. Moreover, it possesses very fast implementation, lending itself useful for real time applications.
2036044
Watermarking JBIG2 text region for image authentication
An authentication watermarking technique (AWT) inserts hidden data into an image in order to detect any accidental or malicious alteration to the image. AWT usually computes, using a secret-key, the message authentication code (MAC) of the image, and somehow inserts MAC into the image itself. The authentication verification is performed using the same secret-key used in the insertion. JBIG2 is an international standard for lossy and lossless binary image compression. It decomposes the image into several regions (text, halftone, line-art) and encodes each one using the most appropriate method. This paper proposes a novel data-hiding technique to embed the data into the text region of a JBIG2 file. We, then, use it to create an AWT for a JBIG2-encoded image. The embedded data can be extracted from either the JBIG2 file itself or the binary image obtained by decoding the JBIG2 file.
7309856
Wish branches: combining conditional branching and predication for adaptive predicated execution
Predicated execution has been used to reduce the number of branch mispredictions by eliminating hard-to-predict branches. However, the additional instruction overhead and additional data dependencies due to predicated execution sometimes offset the performance advantage of having fewer mispredictions. We propose a mechanism in which the compiler generates code that can be executed either as predicated code or non-predicated code (i.e., code with normal conditional branches). The hardware decides whether the predicated code or the non-predicated code is executed based on a run-time confidence estimation of the branch's prediction. The code generated by the compiler is the same as predicated code, except the predicated conditional branches are NOT removed - they are left intact in the program code. These conditional branches are called wish branches. The goal of wish branches is to use predicated execution for hard-to-predict dynamic branches and branch prediction for easy-to-predict dynamic branches, thereby obtaining the best of both worlds. We also introduce a class of wish branches, called wish loops, which utilize predication to reduce the misprediction penalty for hard-to-predict backward (loop) branches. We describe the semantics, types, and operation of wish branches along with the software and hardware support required to generate and utilize them. Our results show that wish branches decrease the average execution time of a subset of SPEC INT 2000 benchmarks by 14.2% compared to traditional conditional branches and by 13.3% compared to the best-performing predicated code binary
27330844
Efficient processing of regular path joins using PID
Abstract XML is data that has no fixed structure. So it is hard to design a schema for storing and querying an XML data. Instead of a fixed schema, graph-based data models are widely adopted for querying XML. Queries on XML are based on paths in a data graph. A meaningful query usually has several paths in it, but much of recent research is more concerned with optimizing a single path in a query. In this paper, we present an efficient technique for processing multiple path expressions in a query. We implemented our technique and present preliminary performance results.
15273022
Open Location-Based Service Using Secure Middleware Infrastructure in Web Services
Location-based services or LBS refers to value-added service by processing information utilizing mobile user location. For this kind of LBS, the role of security service is very important in the LBS that store and manage the location information of mobile devices and support various application services using those location information. And in all phases of these functions that include acquisition of location information, storage and management of location information, user management including authentication and information security, and management of the large-capacity location information database, safe security service must be provided. We show the security methods for open LBS in this paper.
1329357
Data Reduction in Support Vector Machines by a Kernelized Ionic Interaction Model
A major drawback of support vector machines is their high computational complexity. In this paper, we introduce a novel kernelized ionic interaction (IoI) model for data reduction in support vector machines. We also present a data reduction method based on the kernelized instance based (KIB2) algorithm. We show that the computation time can be significantly reduced without any significant decrease in the prediction accuracy.
15684093
Efficient Authentication and Authorization of Mobile Users Based on Peer-to-Peer Network Mechanisms
This paper presents a peer-to-peer based authentication and authorization infrastructure to minimize authentication delays when mobile users roam across different wireless networks. The basic idea is to avoid exchanging security information between networks visited by a roaming user and the user's home authentication, authorization, and accounting (AAA) server that is typically located in the home network possibly far away from the visited network. Instead, authentication and authorization of a roaming user shall be supported by an AAA server in the visited network. We propose that the AAA server that is responsible for authentication and authorization in a newly visited network locates the AAA server in the previously visited network and retrieves the required security information from that AAA server. The AAA servers can be organized in a peer-to-peer manner and peer-to-peer mechanisms can be applied for searching and transferring security information between them. We propose several mechanisms for quickly locating the previously responsible AAA server in order to decrease authentication delays. The performance of these mechanisms is evaluated by simulations. Real performance measurements show the rather low performance overhead of application level forwarding used in peer-to-peer networks.