• A Collection of Visual Thesauri for Browsing Large Collections of Geographic Images

      Ramsey, Marshall C.; Chen, Hsinchun; Zhu, Bin (John Wiley & Sons, Inc., 1999)
      Digital libraries of geo-spatial multimedia content are currently deficient in providing fuzzy, concept-based retrieval mechanisms to users. The main challenge is that indexing and thesaurus creation are extremely laborintensive processes for text documents and especially for images. Recently, 800,000 declassified satellite photographs were made available by the United States Geological Survey. Additionally, millions of satellite and aerial photographs are archived in national and local map libraries. Such enormous collections make human indexing and thesaurus generation methods impossible to utilize. In this article we propose a scalable method to automatically generate visual thesauri of large collections of geo-spatial media using fuzzy, unsupervised machine-learning techniques.
    • Creating a Large-Scale Content-Based Airphoto Image Digital Library

      Zhu, Bin; Ramsey, Marshall C.; Chen, Hsinchun (IEEE, 2000-01)
      This paper describes a content-based image retrieval digital library that supports geographical image retrieval over a testbed of 800 aerial photographs, each 25 megabytes in size. In addition, this paper also introduces a methodology to evaluate the performance of the algorithms in the prototype system. The major contributions of this paper are two. 1) We suggest an approach that incorporates various image processing techniques including Gabor filters, image enhancement, and image compression, as well as information analysis technique such as self-organizing map (SOM) into an effective large-scale geographical image retrieval system. 2) We present two experiments that evaluate the performance of the Gaborfilter- extracted features along with the corresponding similarity measure against that of human perception, addressing the lack of studies in assessing the consistency between an image representation algorithm or an image categorization method and human mental model.
    • Creating a Large-Scale Digital Library for Georeferenced Information

      Zhu, Bin; Ramsey, Marshall C.; Ng, Tobun Dorbin; Chen, Hsinchun; Schatz, Bruce R. (1999-07)
      Digital libraries with multimedia geographic content present special challenges and opportunities in today's networked information environment. One of the most challenging research issues for geospatial collections is to develop techniques to support fuzzy, concept-based, geographic information retrieval. Based on an artificial intelligence approach, this project presents a Geospatial Knowledge Representation System (GKRS) prototype that integrates multiple knowledge sources (textual, image, and numerical) to support concept-based geographic information retrieval. Based on semantic network and neural network representations, GKRS loosely couples different knowledge sources and adopts spreading activation algorithms for concept-based knowledge inferencing. Both textual analysis and image processing techniques have been employed to create textual and visual geographical knowledge structures. This paper suggests a framework for developing a complete GKRS-based system and describes in detail the prototype system that has been developed so far.
    • HelpfulMed: Intelligent Searching for Medical Information over the Internet

      Chen, Hsinchun; Lally, Ann M.; Zhu, Bin; Chau, Michael (Wiley Periodicals, Inc, 2003-05)
      Medical professionals and researchers need information from reputable sources to accomplish their work. Unfortunately, the Web has a large number of documents that are irrelevant to their work, even those documents that purport to be â medically-related.â This paper describes an architecture designed to integrate advanced searching and indexing algorithms, an automatic thesaurus, or â concept space,â and Kohonen-based Self-Organizing Map (SOM) technologies to provide searchers with finegrained results. Initial results indicate that these systems provide complementary retrieval functionalities. HelpfulMed not only allows users to search Web pages and other online databases, but also allows them to build searches through the use of an automatic thesaurus and browse a graphical display of medical-related topics. Evaluation results for each of the different components are included. Our spidering algorithm outperformed both breadth-first search and PageRank spiders on a test collection of 100,000 Web pages. The automatically generated thesaurus performed as well as both MeSH and UMLSâ systems which require human mediation for currency. Lastly, a variant of the Kohonen SOM was comparable to MeSH terms in perceived cluster precision and significantly better at perceived cluster recall.
    • Support Concept-based Multimedia Information Retrieval: A Knowledge Management Approach

      Zhu, Bin; Ramsey, Marshall C.; Chen, Hsinchun; Hauck, Roslin V.; Ng, Tobun Dorbin; Schatz, Bruce R. (1999)
      Identified as an important management concept five years ago (Gamer 1999), knowledge management (KM) aims to enable organizations to capture, organize, and access their intellectual assets. This paper proposes a prototype system that applies a knowledge management approach to support concept-based multimedia information retrieval by integrating various information analysis and image processing techniques. The proposed system uses geographical information as its testbed and aims to provide flexibility to users in terms of specifying their information needs and to facilitate parallel extraction ofinformation in different formats (i.e., text, image). Our testbed selection is based not only on the fact that geographical information has become an important resource supporting organization decision making, but also on the diversity of its information media and the fuzziness of geo-spatial queries. We hope that the proposed system will improve the accessibility of geographical information in different media and provide an example of integrating various information and multimedia techniques to support concept-based cross-media information retrieval.
    • Validating a Geographic Image Retrieval System

      Zhu, Bin; Chen, Hsinchun (Wiley Periodicals, Inc, 2000)
      This paper summarizes a prototype geographical image retrieval system that demonstrates how to integrate image processing and information analysis techniques to support large-scale content-based image retrieval. By using an image as its interface, the prototype system addresses a troublesome aspect of traditional retrieval models, which require users to have complete knowledge of the low-level features of an image. In addition we describe an experiment to validate the performance of this image retrieval system against that of human subjects in an effort to address the scarcity of research evaluating performance of an algorithm against that of human beings. The results of the experiment indicate that the system could do as well as human subjects in accomplishing the tasks of similarity analysis and image categorization. We also found that under some circumstances texture features of an image are insufficient to represent a geographic image. We believe, however, that our image retrieval system provides a promising approach to integrating image processing techniques and information retrieval algorithms.