Multimedia Database Applications Research Articles

Exact and approximate flexible aggregate similarity search

Aggregate similarity search, also known as aggregate nearest-neighbor (Ann) query, finds many useful applications in spatial and multimedia databases. Given a group Q of M query objects, it retrieves from a database the objects most similar to Q, where the similarity is an aggregation (e.g., $${{\mathrm{sum}}}$$sum, $$\max $$max) of the distances between each retrieved object p and all the objects in Q. In this paper, we propose an added flexibility to the query definition, where the similarity is an aggregation over the distances between p and any subset of $$\phi M$$?M objects in Q for some support$$0< \phi \le 1$$0<?≤1. We call this new definition flexible aggregate similarity search and accordingly refer to a query as a flexible aggregate nearest-neighbor ( Fann ) query. We present algorithms for answering Fann queries exactly and approximately. Our approximation algorithms are especially appealing, which are simple, highly efficient, and work well in both low and high dimensions. They also return near-optimal answers with guaranteed constant-factor approximations in any dimensions. Extensive experiments on large real and synthetic datasets from 2 to 74 dimensions have demonstrated their superior efficiency and high quality.

A Hybrid Image Mining Technique using LIMbased Data Mining Algorithm

ABSTRACT The field of image retrieval and mining has become a vibrant research area due to speedy enhancement in the volume of digital image databases. Nowadays, a large portion of information is in visual form; it is essential and certainly pleasing to search for images by content. Image mining has a variety of applications in various sectors like medical diagnosis, biology, remote sensing, space research, etc. This research is to determine the exact images while mining an image (multimedia) database and proposes a novel approach for mining images using LIM based image matching technique with neural networks. This process is independent of too many parameter setting to generate a robust solution. It is designed and implemented on MATLAB and is tested with the images of various databases. Appropriate measures were devised to evaluate the performance of the system. The performances of the LIM based image matching technique results were noteworthy and comparable. While comparing with the number of false retrievals with the correct retrievals, the anticipated system performance level will be suited for several simple day to day multimedia database applications and image mining systems. The image mining system derived from the LIM based image matching technique provided promising results.

Multimedia Database Applications: Issues and Concerns for Classroom Teaching

The abundance of multimedia data and information is challenging educators to effectively search, browse, access, use, and store the data for their classroom teaching. However, many educators could still be accustomed to teaching or searching for information using conventional methods, but often the conventional methods may not function well with multimedia data. Educators need to efficiently interact and manage a variety of digital media files too. The purpose of this study is to review current multimedia database applications in teaching and learning, and further discuss some of the issues or concerns that educators may have while incorporating multimedia data into their classrooms. Some strategies and recommendations are also provided in order for educators to be able to use multimedia data more effectively in their teaching environments.

Adapting metric indexes for searching in multi-metric spaces

An important research issue in multimedia databases is the retrieval of similar objects. For most applications in multimedia databases, an exact search is not meaningful. Thus, much effort has been devoted to develop efficient and effective similarity search techniques. A recent approach that has been shown to improve the effectiveness of similarity search in multimedia databases resorts to the usage of combinations of metrics (i.e., a search on a multi-metric space). In this approach, the desirable contribution (weight) of each metric is chosen at query time. It follows that standard metric indexes cannot be directly used to improve the efficiency of dynamically weighted queries, because they assume that there is only one fixed distance function at indexing and query time. This paper presents a methodology for adapting metric indexes to multi-metric indexes, that is, to support similarity queries with dynamic combinations of metric functions. The adapted indexes are built with a single distance function and store partial distances to estimate the dynamically weighed distances. We present two novel indexes for multimetric space indexing, which are the result of the application of the proposed methodology.

Modeling and Management of Fuzzy Information in Multimedia Database Applications

In this paper, we firstly present a conceptual data model for multimedia database applications based on ExIFO2 model. The ExIFO2 data model is chosen as the conceptual model since it handles complex objects along with their uncertain and imprecise properties. We enhanced this conceptual model in order to meet the multimedia data requirements. In addition to uncertain and imprecise information, we present a way of handling relationships among objects of multimedia database applications. Events that might be extracted from video or audio are also considered in this study. Secondly, the conceptual model is mapped to a logical model, which the fuzzy object-oriented data (FOOD) model is chosen, for storing and manipulating the multimedia objects. This mapping is done in a way that it preserves most of the information represented at the conceptual level. Finally, in this study videos of football (soccer) games is selected as the multimedia database application to show how we handle crisp and fuzzy querying and retrieval of fuzzy and crisp data from the database. A program has been developed to draw ExIFO2 schemas and to map the schema to FOOD code automatically.

Adaptive and incremental processing for distance join queries

A spatial distance join is a relatively new type of operation introduced for spatial and multimedia database applications. Additional requirements for ranking and stopping cardinality are often combined with the spatial distance join in online query processing or Internet search environments. These requirements pose new challenges as well as opportunities for more efficient processing of spatial distance join queries. In this paper, we first present an efficient k-distance join algorithm that uses spatial indexes such as R-trees. Bidirectional node expansion and plane-sweeping techniques are used for fast pruning of distant pairs, and the plane-sweeping is further optimized by novel strategies for selecting a sweeping axis and direction. Furthermore, we propose adaptive multistage algorithms for k-distance join and incremental distance join operations. Our performance study shows that the proposed adaptive multistage algorithms outperform previous work by up to an order of magnitude for both k-distance, join and incremental distance join queries, under various operational conditions.

A shape-based image retrieval method using salient edges

Content-based image retrieval is emerging as an important research area with applications in digital libraries and multimedia databases. In this paper, we present a novel five-stage image retrieval method based on salient edges. In the first stage, the Canny operator is performed to detect edge points. Then, the Water-Filling algorithm is employed to extract edge curves. In the third stage, salient edges are selected and the shape features in terms of the salient edges are yielded. In the fourth stage, a similarity measure, namely the integrated salient edge matching, that integrates properties of all the salient edges, is introduced, and used to compare the similarity of the query image with the images in the database. Finally, the best matches are returned in similarity order. The presented approach is easy to implement and can be efficiently applied to retrieve images with clear edges. Preliminary experimental results on a database containing 6500 images are very promising.

Building scholarly online multimedia collections and services

This paper outlines the evolution of an approach to building multimedia database applications for research and learning in an Australian university. This has involved an ongoing collaboration between the library, as database developer, together with research scholars and course managers, as application directors and discipline consultants. The paper provides details of three particular projects, the Australian Zooarchaeology image database, the fourteenth century music database and Audio Visual online. Each application has used the technological infrastructure provided by the library to develop unique and successful approaches to research and learning. All, in different ways, take advantage of the many new multimedia capabilities of the WWW and suggest that such an approach could be developed into a working model for building sustainable quality multimedia Web resources for research and learning.

Adaptive multi-stage distance join processing

A spatial distance join is a relatively new type of operation introduced for spatial and multimedia database applications. Additional requirements for ranking and stopping cardinality are often combined with the spatial distance join in on-line query processing or internet search environments. These requirements pose new challenges as well as opportunities for more efficient processing of spatial distance join queries. In this paper, we first present an efficient k -distance join algorithm that uses spatial indexes such as R-trees. Bi-directional node expansion and plane-sweeping techniques are used for fast pruning of distant pairs, and the plane-sweeping is further optimized by novel strategies for selecting a sweeping axis and direction. Furthermore, we propose adaptive multi-stage algorithms for k -distance join and incremental distance join operations. Our performance study shows that the proposed adaptive multi-stage algorithms outperform previous work by up to an order of magnitude for both k -distance join and incremental distance join queries, under various operational conditions.

Interfacing reprogrammable universal remote controller with multimedia PC

The paper describes the design and implementation of a low-cost electronic circuit which can be incorporated into a universal remote controller that is used to control electronic appliances such as televisions, video cassette recorders and audio systems. In an educational or a conference environment, the circuit can be used to facilitate computer-assisted presentations by acting as an interface between the universal remote controller and a personal computer (PC) so that multimedia database applications can be developed on a PC to retrieve desired video clips on a video cassette tape and play them on a TV via the universal remote controller.1998 Academic Press

KMeD: A knowledge-based multimedia medical distributed database system

The objectives of the Knowledge-Based Multimedia Medical Distributed Database System (KMeD) are to: query medical multimedia distributed databases by both image content and alphanumeric content; model the temporal, spatial, and evolutionary nature of medical objects; formulate queries using conceptual and imprecise medical terms and support cooperative processing; develop a domain-independent, high-level query language and a medical domain user interface to support KMeD functionality; and provide analysis and presentation methods for visualization of knowledge and data models. Using rules derived from application and domain knowledge, approximate and conceptual queries may be answered. These concepts are validated in a testbed linked with radiology image databases. The joint research between the UCLA Computer Science Department and the School of Medicine assures that the prototype system is of direct interest to medical research and practice. The results of this research are extensible to other multimedia database applications.

TESSA—an image testbed for evaluating 2-D spatial similarity algorithms

In multimedia database applications, a major class of users' requests require retrieving those images in the database that are spatially similar to the query image. To process such queries, a spatial similarity algorithm is required. A spatial similarity algorithm assesses the degree to which the spatial relationships among the domain objects in a database image conform to those specified in the query image. The recent ubiquitous interest in multimedia information systems has spurred a great interest in spatial similarity algorithms. A standard testbed of images is required not only to systematically evaluate these algorithms but also to compare and contrast them. However, there is no such testbed of images available for this purpose.In this paper, we describe a collection of images, referred to as TESSA, as a testbed for investigating the robustness of spatial similarity algorithms and their further use in evaluating the retrieval effectiveness of these algorithms. The TESSA collection comprises 160 images and are produced by generating 15 variants of each of the 10 original images. Image variants are produced by scale, rotation, and translation, and by an arbitrary composition of these three transformations. The variants are designed to inquire into the robustness of spatial similarity algorithms. To facilitate their further use in evaluating the retrieval effectiveness, each image in TESSA is considered as a query in turn, and an expert is asked to provide a rank ordering of the TESSA images with respect to the query image vis-a-vis expert provided rank ordering. System provided rank ordering for a query image is the rank ordering of TESSA images induced by a spatial similarity algorithm with respect to the query. Retrieval effectiveness of spatial similarity algorithms is then characterized by using R norm measure. This measure is based on both the expert and system provided rank orderings.

Call for papers for a special issue on Content Based Retrieval

Content analysis and understanding is an emerging area of multimedia research. Multimedia database applications are ready to leapfrog from handling simple BLOBS to retrieving information based on content understanding. The Multimedia Systems journal identifies this area as a significant research topic and invites original, unpublished contributions highlighting the issue, research results or applications in the area of Content Based Retrieval.