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Access to Pictorial Material: A Review of Current Research and Future Prospects

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Abstract

Rapid expansion in the digitization of image and image collections has vastly increased the numbers of images available to scholars and researchers through electronic means. This research review will familiarize the reader with current research applicable to the development of image retrieval systems and provides additional material for exploring the topic further, both in print and online. The discussion will cover several broad areas, among them classification and indexing systems used for describing image collections and research initiatives into image access focusing on image attributes, users, queries, tasks, and cognitive aspects of searching. Prospects for the future of image access, including an outline of future research initiatives, are discussed. Further research in each of these areas will provide basic data which will inform and enrich image access system design and will hopefully provide a richer, more flexible, and satisfactory environment for searching for and discovering images. Harnessing the true power of the digital image environment will only be possible when image retrieval systems are coherently designed from principles derived from the fullest range of applicable disciplines, rather than from isolated or fragmented perspectives.

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References

  • Ahuja, N. “Texture analysis”. In Encyclopedia of Artificial Intelligence. Ed. S. C. Shapiro, New York: Wiley, 1992, pp. 1101–1115.

    Google Scholar 

  • Albrechtsen, H. “Subject Analysis and Indexing: From Automated Indexing to Domain Analysis.” The Indexer 18 (1993), 219–224.

    Google Scholar 

  • Armitage, L. H. and P. G. Enser. “Analysis of User Need in Image Archives.” Journal of Information Science, 23(4) (1997), 287–299.

    Google Scholar 

  • Bakewell, E. Object, Image, Inquiry: The Art Historian at Work. Santa Monica, Calif., AHIP, 1988.

    Google Scholar 

  • Bates, M. J. “The Design of Browsing and Berrypicking Techniques for the Online Search Interface.” Online Review, 13 (1989) 407–424.

    Google Scholar 

  • Batley, S. Visual Information Retrieval: Browsing Strategies in Pictorial Databases, Ph.D., University of Aberdeen, 1988.

  • Berlin, B. and P. Kay. Basic Color Terms. Berkeley, University of California Press, 1969.

    Google Scholar 

  • Besser, H. “Visual Access to Visual Images — The UC Berkeley Image Database Project.” Library Trends (38) (1990), 787–798.

  • Besser, H. and M. Snow. “Access to Diverse Collections in University Settings: The Berkeley Dilemma.” In Beyond the book: Extending MARC for Subject Access. Eds. T. Petersen and P. Molholt, Boston: G. K. Hall, 1990, pp. 203–224.

    Google Scholar 

  • Chang, S. F. and J. R. Smith. “Visual Information Retrieval from Large Distributed Online Repositories.” Communications of the ACM 1997, 40(12) (1997), 63–71.

    Google Scholar 

  • Domeshek, E. and S. Kedar. Interactive Information Retrieval Systems with Minimalist Representation. AAAI-96: Thirteenth National Conference on Artificial Intelligence, Portland, OR, 1996.

  • Drabenstott, K. M. Subject Access to Visual Resources Collections: A Model for Computer Construction of Thematic Catalogs. New York: Greenwood Press, 1986.

    Google Scholar 

  • Dunlop, M. D. Multimedia Information Retrieval, University of Glasgow, 1991.

  • Ellis, D. The Derivation of a Behavioural Model for Information Retrieval System Design, University of Sheffield, 1987.

  • Enser, P. G. B. “Query Analysis in a Visual Information Retrieval Context.” Journal of Document and Text Management 1(1) (1993), 25–52.

    Google Scholar 

  • Evans, H. Picture Librarianship. New York: K. G. Saur, 1980.

    Google Scholar 

  • Fidel, R. “The Image Retrieval Task: Implications for the Design and Evaluation of Image Databases.” The New Review of Hypermedia and Multimedia 3 (1997), 181–199.

    Google Scholar 

  • Frost, O. “The University of Michigan School of Information Art Image Browser: Designing and Testing a Model for Image Retrieval.” Knowledge Organization and Change. Ed. R. Green. Frankfurt/Main, Indeks Verlag, 5 (1996), 182–188.

    Google Scholar 

  • Gilbert, K. D. Picture Indexing for Local History Materials. Monroe NY: Library Research Associates, 1973.

    Google Scholar 

  • Gordon, A. S. The Design of Knowledge-Rich Browsing Interfaces for Retrieval in Digital Libraries, Ph.D., Northwestern University, 1998.

  • Green, S. J. The Classification of Pictures and Slides. Denver CO: Little Books, 1984.

    Google Scholar 

  • Greenberg, J. “Intellectual control of visual archives: A comparison between the Art and Architecture Thesaurus and Library of Congress Thesaurus for Graphic Materials.” Cataloging & Classification Quarterly 16(1) (1993), 85–117.

    Google Scholar 

  • Gupta, A. and S. Santini. “In Search of Information in Visual Media.” Communications of the ACM 40(12) (1997), 34–42.

    Google Scholar 

  • Haralick, R. M. “Statistical and Structural Approaches to Texture.” Proceedings IEEE 67 (1979), 786–804.

    Google Scholar 

  • Hastings, S. K. An Exploratory Study of Intellectual Access to Digitized Art Images, Ph.D., The Florida State University, 1994.

  • Hibler, J. N. D. and C. H. Leung. Image Storage and Retrieval Systems. Proceedings-SPIE, the International Society for Optical Engineering, San Jose, CA., 1992.

  • Holt, B. and K. Weiss. Proceedings of the 60th ASIS Annual Meeting. ASIS '97, Washington, D.C., Information Today, Inc., 1997.

  • Hourihane, C. “A Selective Survey of Systems of Subject Classification.” Computers and the History of Art. Eds. W. Vaughan, A. Hamber and J. Miles. London: Mansell Publishing Limited, 1989, pp. 117–129.

    Google Scholar 

  • Jörgensen, C. Image Attributes: An Investigation, Ph.D. Syracuse University, 1995.

  • Jörgensen, C. Proceedings of the 6th ASIS SIG/CR Classification Research Workshop. Classification Research Workshop, Chicago IL, American Society for information Science Special Interest Group/Classification Research, 1995.

  • Jörgensen, C. “The Applicability of Existing Classification Systems to Image Attributes: A Selected Review.” Knowledge Organization and Change. Ed. R. Green. Frankfurt/Main, Indeks Verlag, 5 (1996), 189–197.

    Google Scholar 

  • Julesz, B. “Textons, the Elements of Texture Perception and Their Interactions.” Nature 290 (1981), 9–97.

    Google Scholar 

  • Keister, L. H. “User Types and Queries: Impact on Image Access Systems.” Challenges in Indexing Electronic Text and Images. Eds. R. Fidel, T. B. Hahn, E. M. Rasmussen and P. J. Smith. Medford NJ, Learned Information, Inc., 1994.

    Google Scholar 

  • Korf Vidal, N. Experimental Image Taxonomy: An Inquiry into Spontaneous Image Organization, Master's Thesis, Cornell University, 1995.

  • Lancaster, F. W. “Indexing Multimedia Sources.” Indexing and Abstracting in Theory and Practice. Champaign IL, University of Illinois Graduate School of Library and Information Science, 1998, pp. 206–221.

    Google Scholar 

  • Lassaline, M. E. and E. J. Wisniewski. “Basic Levels in Artificial and Natural Categories: Are All Basic Levels Created Equal?” Percepts, Concepts, and Categories: The Representation and Processing of Information. Ed. B. Burns. New York: North-Holland, 93, 1992.

    Google Scholar 

  • Lockhead, G. R. “On Identifying Things.” Percepts, Concepts, and Categories: The Representation and Processing of Information. Ed. B. Burns, New York: North-Holland, 93 (1992), 109–143.

    Google Scholar 

  • Lohse, G. L. and K. Biolsi. “A Classification of Visual Representations.” Communications of the ACM 37(12) (1994), 36–49.

    Google Scholar 

  • Medin, D. L. and W. D. Wattenmaker. “Category Cohesiveness, Theories, and Cognitive Archeology.” Concepts and Conceptual Development: Ecological and Intellectual Factors in Categorization. Ed. U. Neisser, New York: Cambridge University Press, 1987, pp. 25–62.

    Google Scholar 

  • Okon, C. “IBM's Image Recognition Tech for Databases at Work: QBIC.” Advanced Imaging, 1995, pp. 63–65.

  • Panofsky, E. Studies in Iconology. New York: Harper & Row, 1962.

    Google Scholar 

  • Parker, E. B. LC Thesaurus for Graphic Materials: Topical Terms for Subject Access. Washington, D. C.: Library of Congress, 1987.

    Google Scholar 

  • Rasmussen, E. M. “Indexing Images.” Annual Review of Information Science and Technology (ARIST). Ed. M. E. Williams, Medford NJ: Information Today, Inc., 32 (1997), 169–196.

    Google Scholar 

  • Roddy, K. “Subject Access to Visual Resources: What the 90s Might Portend.” Library Hi Tech, 9(1) (1991), 45–49.

    Google Scholar 

  • Romer, D. Getty Information Institute Online Conference on Digitizing Technologies, 1995.

  • Romer, D. M. A Keyword is Worth 1,000 Images. Rochester, NY: Kodak, Inc., 1993.

    Google Scholar 

  • Rorvig, M. E. and C. H. Turner. The NASA Image Collection Visual Thesaurus. Proceedings. American Society for Information Science 17th Mid-Year Meeting, Ann Arbor, MI, 1988.

  • Rosch, E. and C. B. Mervis. “Basic Objects in Natural Categories.” Cognitive Psychology, 8 (1976), 382–439.

    Google Scholar 

  • Seloff, G. A. “Automated Access to the NASA-JSC Image Archive.” Library Trends, 38(4) 1990.

  • Shatford, S. “Analyzing the Subject of a Picture: A Theoretical Approach.” Cataloging & Classification Quarterly 6(3) (1986), 39–62.

    Google Scholar 

  • Simons, W. and L. C. Tansey. A Slide Classification System for the Organization and Automatic Indexing of Interdisciplinary Collections of Slides and Pictures. Santa Cruz CA, University of California, 1970.

    Google Scholar 

  • Sledge, J. Points of View. Multimedia Computing and Museums. Philadelphia, Archives & Museum Informatics, 1995, pp. 335–346.

    Google Scholar 

  • Smith, E. E. and G. J. Balzano. “Nominal, Perceptual, and Semantic Codes in Picture Categorization.” Semantic Factors in Cognition Eds. J.W. Cotton and R. L. Klatzky, Hillsdale, NJ: Lawrence Erlbaum Associates, 1978, pp. 137–168.

    Google Scholar 

  • Soergel, D. “The Art and Architecture Thesaurus (AAT): A Critical Appraisal.” Visual Resources 10 (1995), 369–400.

    Google Scholar 

  • Stam, D. C. “The Quest for a Code, or a Brief History of the Computerized Cataloging of Art Object.” Art Documentation 8 (1989), 7–15.

    Google Scholar 

  • Stam, D. C. and A. Giral. “Linking Art Objects and Art Information.” Library Trends, 37(2) (1988), 117–264.

    Google Scholar 

  • Svenonius, E. Thesauri. Automatic Processing of Art History Data and Documents. Eds. L. Corti and M. Schmitt. Los Angeles: The J. Paul Getty Trust, 1984, pp. 33–48.

    Google Scholar 

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Jörgensen, C. Access to Pictorial Material: A Review of Current Research and Future Prospects. Computers and the Humanities 33, 293–318 (1999). https://doi.org/10.1023/A:1002065412222

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