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A Unified Approach to Data Modeling and Retrieval for a Class of Image Database Applications

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Book cover Multimedia Database Systems

Part of the book series: Artificial Intelligence ((AI))

Summary

Recently, there has been widespread interest in various kinds of database management systems for managing information from images. Image Retrieval problem is concerned with retrieving images that are relevant to users’ requests from a large collection of images, referred to as the image database. Since the application areas are very diverse, there seems to be no consensus as to what an image database system really is. Consequently, the characteristics of the existing image database systems have essentially evolved from domain specific considerations [20]. In response to this situation, we have introduced a unified framework for retrieval in image databases in [17]. Our approach to the image retrieval problem is based on the premise that it is possible to develop a data model and an associated retrieval model that can address the needs of a class of image retrieval applications. For this class of applications, from the perspective of the end users, image processing and image retrieval are two orthogonal issues and this distinction contributes toward domain-independence. In this paper, we analyze the existing approaches to image data modeling and establish a taxonomy based on which these approaches can be systematically studied and understood. Then we investigate a class of image retrieval applications from the view point of their retrieval requirements to establish both a taxonomy for image attributes and generic retrieval types. To support the generic retrieval types, we have proposed a data model/framework referred to as AIR. AIR data model employs multiple logical representations. The logical representations can be viewed as abstractions of physical images at various levels. They are stored as persistent data in the image database. We then discuss how image database systems can be developed based on the AIR framework. Development of two image database retrieval applications based on our implementation of AIR framework are briefly described. Finally, we identify several research issues in AIR and our proposed solutions to some of them are indicated.

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Author information

Authors and Affiliations

  1. Department of Electrical Engineering and Computer Science, Ohio University, Athens, OH, 45701, USA

    Venkat N. Gudivada

  2. The Center for Advanced Computer Studies, University of Southwestern Louisiana, Lafayette, LA, 70504, USA

    Vijay V. Raghavan & Kanonluk Vanapipat

Authors
  1. Venkat N. Gudivada
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  2. Vijay V. Raghavan
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  3. Kanonluk Vanapipat
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Editor information

Editors and Affiliations

  1. Computer Science Department, University of Maryland, College Park, MD, 20742, USA

    V. S. Subrahmanian

  2. Dept. of Information and Software Systems Engineering, George Mason University, VA, 22030, Fairfax, USA

    Sushil Jajodia

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© 1996 Springer-Verlag Berlin Heidelberg

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Gudivada, V.N., Raghavan, V.V., Vanapipat, K. (1996). A Unified Approach to Data Modeling and Retrieval for a Class of Image Database Applications. In: Subrahmanian, V.S., Jajodia, S. (eds) Multimedia Database Systems. Artificial Intelligence. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-60950-3_2

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  • DOI: https://doi.org/10.1007/978-3-642-60950-3_2

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-64622-5

  • Online ISBN: 978-3-642-60950-3

  • eBook Packages: Springer Book Archive

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