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Rotation invariant indexing of shapes and line drawings
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Source Conference on Information and Knowledge Management archive
Proceedings of the 14th ACM international conference on Information and knowledge management table of contents
Bremen, Germany
SESSION: Paper session KM-2 (knowledge management): index structures table of contents
Pages: 131 - 138  
Year of Publication: 2005
ISBN:1-59593-140-6
Authors
Michail Vlachos  IBM T.J. Watson Research Center
Zografoula Vagena  University of California Riverside
Philip S. Yu  IBM T.J. Watson Research Center
Vassilis Athitsos  Boston University
Sponsors
ACM: Association for Computing Machinery
SIGIR: ACM Special Interest Group on Information Retrieval
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 8,   Downloads (12 Months): 77,   Citation Count: 4
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ABSTRACT

We present data representations, distance measures and organizational structures for fast and efficient retrieval of similar shapes in image databases. Using the Hough Transform we extract shape signatures that correspond to important features of an image. The new shape descriptor is robust against line discontinuities and takes into consideration not only the shape boundaries, but also the content inside the object perimeter. The object signatures are eventually projected into a space that renders them invariant to translation, scaling and rotation. In order to provide support for real-time query-by-content, we also introduce an index structure that hierarchically organizes compressed versions of the extracted object signatures. In this manner we can achieve a significant performance boost for multimedia retrieval. Our experiments suggest that by exploiting the proposed framework, similarity search in a database of 100,000 images would require under 1 sec, using an off-the-shelf personal computer.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Marvel: Multimedia analysis and retrieval system. http://www.research.ibm.com/marvel/.
 
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P. Fränti, A. Mednonogov, V. Kyrki, and H. Kälviäinen. Content-based matching of line-drawing images using the Hough transform. In IJDAR(3), No. 2, 2000.
 
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S. Tabbone, L. Wendling, and K. Tombre. Matching of graphical symbols in line-drawing images using angular signature information. In IJDAR(6), No. 2, 2003.
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W. Zorski, B. Foxon, J. Blackledge, and M. Turner. Fingerprint and iris identification method based on the hough transform. In Proc. of Imaging and Digital Image Processing, pages 69-81, 2000.


Collaborative Colleagues:
Michail Vlachos: colleagues
Zografoula Vagena: colleagues
Philip S. Yu: colleagues
Vassilis Athitsos: colleagues