5568199
Transform features for texture classification and discrimination in large image databases
Proposes a method for classification and discrimination of textures based on the energies of image subbands. The authors show that with this relatively simple feature set, effective texture discrimination can be achieved. In the paper, subband-energy feature sets extracted from the following typical image decompositions are compared: wavelet subband, uniform subband, discrete cosine transform (DCT), and spatial partitioning. The authors report that over 90% correct classification was attained using the feature set in classifying the full Brodatz [1965] collection of 112 textures. Furthermore, the subband energy-based feature set can be readily applied to a system for indexing images by texture content in image databases, since the features can be extracted directly from spatial-frequency decomposed image data. The authors also show that to construct a suitable space for discrimination, Fisher discrimination analysis (Dillon and Goldstein, 1984) can be used to compact the original features into a set of uncorrelated linear discriminant functions. This procedure makes it easier to perform texture-based searches in a database by reducing the dimensionality of the discriminant space. The authors also examine the effects of varying training class size, the number of training classes, the dimension of the discriminant space and number of energy measures used for classification. The authors hope that the performance for texture discrimination of these simple energy-based features will allow images in a database to be efficiently and effectively indexed by contents of their textured regions.<<ETX>>
2339969
Interactive search fusion methods for video database retrieval
In this paper, we investigate a new method for video database retrieval using interactive search fusion. Recent video analysis techniques have enabled the extraction of a variety of descriptors of features, concepts, clusters, classification results, speech and textual terms, MPEG-7 metadata, and so on. However, given an information need users are faced with a daunting task of trying to formulate queries over these multiple disparate data sources in order to retrieve the desired video content. In this paper, we explore a novel approach based on search fusion in which the user interactively builds a query by sequentially choosing among the descriptors and data sources and by selecting from various combining and score aggregation functions to fuse results of individual searches. For example, the system allows building of queries such as "retrieve video clips that have color of beach scenes, the detection of sky, and detection of water". In this paper we present the search fusion method and evaluate the performance on a large video database.
1805433
MPEG-7 MDS Content Description Tools and Applications
In this paper, we present the tools specified by the MDS part of the MPEG-7 standard for describing multimedia data such as images and video. In particular, we focus on the description tools that represent the structure and semantics of multimedia data to whose development we have actively contributed. We also describe some of our research prototype systems dealing with the extraction and application of MPEG-7 structural and semantic descriptions. These systems are AMOS, a video object segmentation and retrieval system, and IMKA, an intelligent multimedia knowledge application using the MediaNet knowledge representation framework.
30741426
Multimedia database management systems
Introduction. Multimedia Data Types and Formats. Multimedia Database Design Issues. Text Document Indexing and Retrieval. Indexing and Retrieval of Audio. Image Indexing and Retrieval. Video Indexing and Retrieval. Integrated Multimedia Indexing and Retrieval. Techniques and Data Structures for Efficient Multimedia Similarity Search. System Support for Distributed Multimedia Databases. Measurement of Multimedia Information Retrieval Effectiveness. Products, Applications, and New Developments.
20964781
Special Issue on Image Understanding for Digital Photographs
15943562
Content-based transcoding of images in the Internet
We present a system for transcoding images in the Internet in order to improve their delivery to client devices with a wide range of communication, processing, storage and display capabilities. The content-based image transcoder analyzes the images in order to classify them into image type and image purpose classes. The system then utilizes transcoding policies based on the content classes to manipulate and transcode the images. We describe the image transcoding process for a variety of client devices, including PDAs, hand-held computers (HHCs), TV browsers and color PCs, and demonstrate improvements in delivery speed and accessibility of the images in the Internet.
11571148
Security in Active Networks
The desire for flexible networking services has given rise to the concept of "active networks." Active networks provide a general framework for designing and implementing network-embedded services, typically by means of a programmable network infrastructure. A programmable network infrastructure creates significant new challenges for securing the network infrastructure. 
 
This paper begins with an overview of active networking. It then moves to security issues, beginning with a threat model for active networking, moving through an enumeration of the challenges for system designers, and ending with a survey of approaches for meeting those challenges. The Secure Active Networking Environment (SANE) realizes many of these approaches; an implementation exists and provides acceptable performance for even the most aggressive active networking proposals such as active packets (sometimes called "capsules"). 
 
We close the paper with a discussion of open problems and an attempt to prioritize them.
37610017
Validated Cost Models for Parallel OQL Query Processing
Query cost models are widely used, both for performance analysis and for comparing execution plans during query optimisation. In essence, a cost modelp redicts where time is being spent during query evaluation. Although many cost models have been proposed, for serial, parallel and distributed database systems, surprisingly few of these have been validated against real systems. This paper presents cost models for the parallel evaluation of ODMG OQL queries, which have been compared with experimental results obtained using the Polar object database system. The paper describes the validation of the cost model for a collection of queries, using three join algorithms over the OO7 benchmark database. The results show that the cost model generally both ranks alternative plans appropriately, and gives a useful indication of the response times that can be expected from a plan. The paper also illustrates the application of the cost model by highlighting the contributions of different features and operations to query response times.
13961662
Improving Nearest Neighbor Classifier Using Tabu Search and Ensemble Distance Metrics
The nearest-neighbor (NN) classifier has long been used in pattern recognition, exploratory data analysis, and data mining problems. A vital consideration in obtaining good results with this technique is the choice of distance function, and correspondingly which features to consider when computing distances between samples. In this paper, a new ensemble technique is proposed to improve the performance of NN classifier. The proposed approach combines multiple NN classifiers, where each classifier uses a different distance function and potentially a different set of features (feature vector). These feature vectors are determined for each distance metric using Simple Voting Scheme incorporated in Tabu Search (TS). The proposed ensemble classifier with different distance metrics and different feature vectors (TS-DF/NN) is evaluated using various benchmark data sets from UCI Machine Learning Repository. Results have indicated a significant increase in the performance when compared with various well-known classifiers. Furthermore, the proposed ensemble method is also compared with ensemble classifier using different distance metrics but with same feature vector (with or without Feature Selection (FS)).
29643487
Stochastic network evacuation models
Abstract Stochastic network evacuation models are crucial for the safe evacuation of occupants from buildings. In this paper, we compare an analytical closed queueing network and a simulation model for analyzing the evacuation of occupants from a hospital. Evacuation times, arc congestion, and optimization of the evacuation routes and staff assigned to the evacuation network are included.
16057397
Measuring and modelling the performance of a parallel ODMG compliant object database server
Object database management systems (ODBMSs) are now established as the database management technology of choice for a range of challenging data intensive applications. Furthermore, the applications associated with object databases typically have stringent performance requirements, and some are associated with very large data sets. An important feature for the performance of object databases is the speed at which relationships can be explored. In queries, this depends on the effectiveness of different join algorithms into which queries that follow relationships can be compiled. This paper presents a performance evaluation of the Polar parallel object database system, focusing in particular on the performance of parallel join algorithms. Polar is a parallel, shared-nothing implementation of the Object Database Management Group (ODMG) standard for object databases. The paper presents an empirical evaluation of queries expressed in the ODMG Query Language (OQL), as well as a cost model for the parallel algebra that is used to evaluate OQL queries. The cost model is validated against the empirical results for a collection of queries using four different join algorithms, one that is value based and three that are pointer based. Copyright © 2005 John Wiley & Sons, Ltd.