36995505
Fast and accurate binary halftone image resolution increasing by decision-tree learning
Digital halftone is the technique used to convert gray-scale images into binary ones, simulating gray shades by scattering appropriately black and white pixels. Sometimes, there arises the necessity of increasing the resolution of a halftone image. Some recent works have proposed a number of learning-based techniques to zoom binary images. However, they cannot consider a large neighborhood to decide the colors of the resolution-increased pixels, because their running time skyrockets with the growth of the window and the sample images sizes. The use of large window and samples is required to zoom halftone images accurately. This paper presents a new technique to zoom quickly and precisely images generated by any locally-decided halftone algorithm. It is based on decision-tree learning and it is very fast, even using a large window or large samples. The zoomed images obtained by this technique are incredibly sharp and accurate.
7501741
A new public-key authentication watermarking for binary document images resistant to parity attacks
An authentication watermarking technique (AWT) inserts some hidden data into an image in order to detect any accidental or malicious image alteration. Recent papers have proposed some cryptography-based AWTs for binary and halftone images, but none of them seems to be well-suited for public-key authentication of binary document images. Many of the previous public-key AWTs for binary images can be assaulted by "parity attacks." This paper proposes a new AWT for binary document images that can detect any modification of the watermarked document, even a single pixel flipping. Moreover, both its secretand public-key versions are completely immune against parity attacks. Document images watermarked by the proposed technique present high visual quality, without salt-and-pepper noise.
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.
13935279
Robust anisotropic diffusion to produce clear statistical parametric map from noisy fMRI
Functional magnetic resonance imaging (fMRI) uses MRI to noninvasively map areas of increased neuronal activity in human brain without the use of an exogenous contrast agent. Low signal-to-noise ratio of fMRI images makes it necessary to use sophisticated image processing techniques, such as statistical parametric map (SPM), to detect activated brain areas. This paper presents a new technique to obtain clear SPM from noisy fMRI data. It is based on the robust anisotropic diffusion. A direct application of the anisotropic diffusion to fMRI does not work, mainly due to the lack of sharp boundaries between activated and non-activated regions. To overcome this difficulty, we propose to calculate SPM from noisy fMRI, compute diffusion coefficients in the SPM space, and then perform the diffusion in fMRI images using the coefficients previously computed. These steps are iterated until the convergence. Experimental results using the new technique yielded surprisingly sharp and noiseless SPMs.
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.
15509328
New features for affine-invariant shape classification
An object seen from different viewpoints results in differently deformed images. Affine-invariant shape classification must classify correctly the object, regardless its viewpoint. In this paper, we propose new local and global features invariant under affine transformation. These features can be used for supervised or unsupervised shape classification, and for shape-based image indexing and retrieval. One of the proposed features is related to the convex deficiency and the others are extracted from the area matrix. Area matrix was used by Shen for the similarity matching in image retrieval. However, differently from the Shen's work, we parameterize the shape contour using the affine-length parameter. This makes our features robust to affine parameterization, while Shen's work does not have this property. Experimental results indicate that our method can classify correctly even highly deformed and noisy shapes using small training sets.
13287397
An analysis of the performance impact of wrong-path memory references on out-of-order and runahead execution processors
High-performance, out-of-order execution processors spend a significant portion of their execution time on the incorrect program path even though they employ aggressive branch prediction algorithms. Although memory references generated on the wrong path do not change the architectural state of the processor, they affect the arrangement of data in the memory hierarchy. This paper examines the effects of wrong-path memory references on processor performance. It is shown that these references significantly affect the IPC (instructions per cycle) performance of a processor. Not modeling them leads to errors of up to 10 percent (4 percent on average) in IPC estimates for the SPEC CPU2000 integer benchmarks on an out-of-order processor and errors of up to 63 percent on a runahead-execution processor. In general, the error in the IPC increases with increasing memory latency and instruction window size. We find that wrong-path references are usually beneficial for performance because they prefetch data that is used by later correct-path references. L2 cache pollution is found to be the most significant negative effect of wrong-path references. Code examples are shown to provide insights into how wrong-path references affect performance. We also show that it is crucial to model wrong-path references to accurately estimate the performance improvement provided by runahead execution.
2255453
TCP offload through connection handoff
This paper presents a connection handoff interface between the operating system and the network interface. Using this interface, the operating system can offload a subset of TCP connections in the system to the network interface, while the remaining connections are processed on the host CPU. Offloading can reduce computation and memory bandwidth requirements for packet processing on the host CPU. However, full TCP offloading may degrade system performance because finite processing and memory resources on the network interface limit the amount of packet processing and the number of connections. Using handoff, the operating system controls the number of offloaded connections in order to fully utilize the network interface without overloading it. Handoff is transparent to the application, and the operating system may choose to offload connections to the network interface or reclaim them from the interface at any time. A prototype system based on the modified FreeBSD operating system shows that handoff reduces the number of instructions and cache misses on the host CPU. As a result, the number of CPU cycles spent processing each packet decreases by 16--84%. Simulation results show handoff can improve web server throughput (SEPCweb99) by 15%, despite short-lived connections.
41825214
XKMS-Based Key Management for Open LBS in Web Services Environment
As the killer application of the wireless internet, the LBS (Location-based Services) has reconsidered technology about location determination technology, LBS middleware server for various application, and diverse contents processing technology. 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. This paper describes a key management architecture based on XML standards for securing access to location based information and services. The main characteristic of the approach is that it build on a number of XML-based standards.
6362737
Further progress in watermark evaluation testbed (WET)
While Digital Watermarking has received much attention in recent years, it is still a relatively young technology. There are few accepted tools/metrics that can be used to evaluate the suitability of a watermarking technique for a specific application. This lack of a universally adopted set of metrics/methods has motivated us to develop a web-based digital watermark evaluation system called the Watermark Evaluation Testbed or WET. There have been more improvements over the first version of WET. We implemented batch mode with a queue that allows for user submitted jobs. In addition to StirMark 3.1 as an attack module, we added attack modules based on StirMark 4.0. For a new image fidelity measure, we evaluate conditional entropy as an image fidelity measure for different watermarking algorithms and different attacks. Also, we show the results of curve fitting the Receiver Operating Characteristic (ROC) analysis data using the Parzen window density estimation. The curve fits the data closely while having only two parameters to estimate.
18707877
An efficient debugging method for message-based parallel programs using static analysis information
Guaranteeing reproducibility and minimizing probe effects are major issues in the parallel program debugging. The paper suggests a new debugging method, called the Detect and Reproduce method, for message-based parallel programs. The proposed method is designed to guarantee the reproducible behaviors of a target program and to alleviate probe effects by reducing both the number of the probes to be inserted into a program and the amount of information gathered by those probes. The proposed method achieves such effects by employing a static analysis technique to detect nondeterminacy. By detecting nondeterminacy before running the program, only a small number of probes are required to assure reproducibility. To analyze message-based programs statically, an MHB (minimal happened before) model is designed to catch the synchronization structures and algorithms have been developed to locate nondeterminacy based on the MHB model. Utilizing the analysis results, probes are inserted only into the places where nondeterminacy is likely to take place.