Artificial Intelligence Lab, Department of MIS, University of Arizona / 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.
| Identifer | oai:union.ndltd.org:arizona.edu/oai:arizona.openrepository.com:10150/105934 |
| Date | January 2000 |
| Creators | Zhu, Bin, Chen, Hsinchun |
| Publisher | Wiley Periodicals, Inc |
| Source Sets | University of Arizona |
| Language | English |
| Detected Language | English |
| Type | Journal Article (Paginated) |
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