Creating a Large-Scale Content-Based Airphoto Image Digital Library

Persistent Link:
http://hdl.handle.net/10150/105813
Title:
Creating a Large-Scale Content-Based Airphoto Image Digital Library
Author:
Zhu, Bin; Ramsey, Marshall C.; Chen, Hsinchun
Citation:
Creating a Large-Scale Content-Based Airphoto Image Digital Library 2000-01, 9(1):163-167 IEEE TRANSACTIONS ON IMAGE PROCESSING
Publisher:
IEEE
Journal:
IEEE TRANSACTIONS ON IMAGE PROCESSING
Issue Date:
Jan-2000
Description:
Artificial Intelligence Lab, Department of MIS, University of Arizona
URI:
http://hdl.handle.net/10150/105813
Submitted date:
2004-08-13
Abstract:
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.
Type:
Journal Article (Paginated)
Language:
en
Keywords:
Evaluation; Digital Libraries
Local subject classification:
National Science Digital Library; NSDL; Artificial intelligence lab; AI lab; Content-based image retrieval; Digital library; Gabor wavelets; Self-organizing map; System evaluation

Full metadata record

DC FieldValue Language
dc.contributor.authorZhu, Binen_US
dc.contributor.authorRamsey, Marshall C.en_US
dc.contributor.authorChen, Hsinchunen_US
dc.date.accessioned2004-08-13T00:00:01Z-
dc.date.available2010-06-18T23:34:53Z-
dc.date.issued2000-01en_US
dc.date.submitted2004-08-13en_US
dc.identifier.citationCreating a Large-Scale Content-Based Airphoto Image Digital Library 2000-01, 9(1):163-167 IEEE TRANSACTIONS ON IMAGE PROCESSINGen_US
dc.identifier.urihttp://hdl.handle.net/10150/105813-
dc.descriptionArtificial Intelligence Lab, Department of MIS, University of Arizonaen_US
dc.description.abstractThis 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.en_US
dc.format.mimetypeapplication/pdfen_US
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.subjectEvaluationen_US
dc.subjectDigital Librariesen_US
dc.subject.otherNational Science Digital Libraryen_US
dc.subject.otherNSDLen_US
dc.subject.otherArtificial intelligence laben_US
dc.subject.otherAI laben_US
dc.subject.otherContent-based image retrievalen_US
dc.subject.otherDigital libraryen_US
dc.subject.otherGabor waveletsen_US
dc.subject.otherSelf-organizing mapen_US
dc.subject.otherSystem evaluationen_US
dc.titleCreating a Large-Scale Content-Based Airphoto Image Digital Libraryen_US
dc.typeJournal Article (Paginated)en_US
dc.identifier.journalIEEE TRANSACTIONS ON IMAGE PROCESSINGen_US
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