Raj S. Acharya

Discrete analytical hyperplanes

This paper presents the properties of the discrete analytical hyperplanes. They are defined analytically in the discrete domain by Diophantine equations. We show that the discrete hyperplane is a generalization of the classical digital hyperplanes. We present original properties such as exact point localization and space tiling. The main result is the links made between the arithmetical thickness of a hyperplane and its topology.

Color clustering techniques for color-content-based image retrieval from image databases

Image retrieval based on color content is an auxiliary function for traditional text-annotated image databases. Most color-based image retrieval systems adopt color histograms as the feature of color content. One of the most important steps in these systems is to reduce histogram dimensions with the least loss in color content. A good clustering technique is vital for this purpose. This paper examines the color conservation property by applying different clustering techniques in perceptually uniform color spaces and different images. For studying color spaces, the perceptual uniform spaces, such as Mathematical Transformation to Munsell system (MTM) and C.I.E. L*a*b*, are investigated. For evaluating clustering techniques, the equalized quantization approach, the hierarchical clustering approach, and the Color-Naming-System (CNS) supervised clustering approach are studied. For analyzing color loss, the error bound, the quantized error in color space conversion, and the average quantized error of 400 color images are explored. An image retrieval application based on color content is shown to demonstrate the difference in applying these clustering techniques. These simulation results suggest that good clustering techniques usually lead to more effective retrieval.

Scheduling multimedia services in a low-power MAC for wireless and mobile ATM networks

This paper describes the design and analysis of the scheduling algorithm for energy conserving medium access control (EC-MAC), which is a low-power medium access control (MAC) protocol for wireless and mobile ATM networks. We evaluate the scheduling algorithms that have been proposed for traditional ATM networks. Based on the structure of EC-MAC and the characteristics of wireless channel, we propose a new algorithm that can deal with the burst errors and the location-dependent errors. Most scheduling algorithms proposed for either wired or wireless networks were analyzed with homogeneous traffic or multimedia services with simplified traffic models. We analyze our scheduling algorithm with more realistic multimedia traffic models based on H.263 video traces and self-similar data traffic. One of the key goals of the scheduling algorithms is simplicity and fast implementation. Unlike the time-stamped based algorithms, our algorithm does not need to sort the virtual time, and thus, the complexity of the algorithm is reduced significantly.

BIOMEDICAL IMAGING MODALITIES: A TUTORIAL

The introduction of advanced imaging technologies has improved significantly the quality of medical care available to patients. Non-invasive imaging modalities allow a physician to make increasingly accurate diagnoses and render precise and measured modes of treatment. Current uses of imaging technologies include laboratory medicine, surgery, radiation therapy, nuclear medicine, and diagnostic radiology. This paper provides an overview of most of the popular imaging modalities currently in clinical use. It is hoped that a general understanding of the modality from which an image is derived will help researchers in the subsequent analysis of the image data.

Approach to query-by-texture in image database systems

This paper presents an approach to texture-based image retrieval which determines image similarity on the basis of the matching of fractal codes. Image fractal codes are generated via a fractal image compression technique that has been recently proposed as an effective image compression method. Each image is represented by a set of self-transformations through which an approximation of the original image can be reconstructed. These self-transformations, which are unique to each image and are semantically rich, are termed fractal codes. An image data model is proposed which constructs each image as a hierarchical structure. Each image is decomposed into block-based segments which are then assembled by a hierarchy on the basis of inclusion relationships. Each segment is then fractally encoded. The fractal codes of an iconic image are used as texture key and are matched with the fractal codes of images in a database by applying searching and matching algorithms to the hierarchies of the database images to locate the segments which best match the fractal codes of the iconic image. Retrievals of both exact and inexact matching of images are supported.

Algorithm for the automated alignment of radiographs for image subtraction

The results of this study indicate that automated alignment of pairs of radiographs produces subtractions that are indistinguishable in quality from subtractions aligned manually by an experienced aligner. In developing the algorithm for automated alignment, care was taken that the criteria used for establishing a window appropriate for testing the quality of alignment were the same for both alignment techniques.

Distributed Quality of Service Routing

The goal of QoS routing algorithms is to find a loopless path that satisfies constraints on QoS parameters such as bandwidth, delay etc. In distributed QoS algorithms, the path computation is shared among various routers in the network. These can be classified into two categories depending on whether the routers maintain a global state or not. Algorithms based on a global state information have less message overhead in terms of finding a path. However they have inherent drawbacks like routing with imprecise global state information, frequent message exchanges to maintain the global state etc. Hence such algorithms are not scalable. On the other hand, algorithms based on a local state information rely on flooding techniques to compute the path. Hence they have high overhead for finding a path. In this paper, we propose a distributed QoS routing algorithm, that maintains a partial global state and finds a path based on this limited information. Experimental results show that, the overhead of our algorithm is lesser than those that rely on flooding. The results also show that the impreciseness introduced does not affect the call admission ratio greatly.

Comparative analysis of wireless ATM channel access protocols supporting multimedia traffic

Extension of multimedia services and applications offered by ATM networks to wireless and mobile users has captured a lot of recent research attention. Research prototyping of wireless ATM networks is currently underway at many leading research and academic institutions. Various architectures have been proposed depending on the intended application domain. Successful implementation of wireless connectivity to ATM services is significantly dependent on the medium access control (MAC) protocol, which has to provide support for multimedia traffic and for quality‐of‐service (QoS) guarantees. The objective of this paper is to investigate the comparative performance of a set of access protocols, proposed earlier in the literature, with more realistic source traffic models. Data traffic is modeled with self‐similar (fractal) behavior. Voice traffic is modeled by a slow speech activity detector (SAD). Video traffic is modeled as a H.261 video teleconference, where the number of ATM cells per video frame is described by a gamma distribution and a first‐order discrete autoregressive process model. A comparison of the protocols based on simulation data is presented. The goal of the paper is to identify appropriate techniques for effectively and efficiently supporting multimedia traffic and QoS. Simulation results show that boundaries between different types of services are necessary for multimedia traffic. Reservation for certain traffic type especially video can significantly improve its quality. Reducing the number of collisions is an important issue for wireless networks since contentions lead not only to potentially high delay but also result in high power consumption.

Surface matching of multimodality image volumes by a fuzzy elastic registration technique

Multimodality image registration is useful in diagnostic imaging and treatment planning for radiation therapy. In this paper, we present a technique which registers the surfaces of two volumes acquired by different medical imaging modalities. We represent the image volumes in terms of their surface elements known as tiles. We identify the fuzzy variables, assign fuzzy membership functions to them and generate a fuzzy rule database. The fuzzy algorithm reduces the discrepancy between the two set of tiles until the surfaces are matched. In order to study the efficacy of our approach, we severely warp a simulated image and register it with its original. We register CT and MR volumes of humanoid phantom images. Finally, we present the results at the end of the article.

Comparison of wavelet transforms and fractal coding in texture-based image retrieval

Image compression techniques based on wavelet and fractal coding have been recognized significantly useful in image texture classification and discrimination. In fractal coding approach, each image is represented by a set of self-transformations through which an approximation of the original image can be reconstructed. These transformations of images can be utilized to distinguish images. The fractal coding technique can be extended to effectively determine the similarity between images. We introduce a joint fractal coding technique, applicable to pairs of images, which can be used to determine the degree of their similarity. Our experimental results demonstrate that fractal code approach is effective for content-based image retrieval. In wavelet transform approach, the wavelet transform decorrelates the image data into frequency domain. Feature vectors of images can be constructed from wavelet transformations, which can also be utilized to distinguish images through measuring distances between feature vectors. Our experiments indicate that this approach is also effective on content-based similarity comparison between images. More specifically, we observe that wavelets transform approach performs more effective on content- based similarity comparison on those images which contain strong texture features, where fractal coding approach performs relatively more uniformly well for various type of images.