Abstract
The retrieval of images from a large database of images is an important and emerging area of research. Here, a technique to retrieve images based on appearance that works effectively across large changes of scale is proposed. The database is initially filtered with derivatives of a Gaussian at several scales. A user defined template is then created from an image of an object similar to those being sought. The template is also filtered using Gaussian derivatives. The template is then matched with the filter outputs of the database images and the matches ranked according to the match score. Experiments demonstrate the technique on a number of images in a database. No prior segmentation of the images is required and the technique works with viewpoint changes up to 20 degrees and illumination changes.
This work was supported in part by the Center for Intelligent Information Retrieval, NSF Grants IRI-9208920, CDA-8922572 and ARPA N66001-94-D-6054
Chapter PDF
Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
References
Myron Flickner, Haxpreet Sawhney, Wayne Niblack, Jonathan Ashley, Qian Huang, Byron Dom, Monika Gorkani, Jim Hafner, Denis Lee, Dragutin Petkovix, David Steele, and Peter Yanker: Query By Image and Video Content: The QBIC System. IEEE Computer Magazine, September 1995, pp.23–30.
Gösta H. Granlund, and Hans Knutsson: Signal Processing in Computer Vision. Kluwer Academic Publishers, 1995, ISBN 0-7923-9530-1, Dordrecht, The Netherlands.
Venkat N. Gudivada, and Vijay V. Raghavan: Content-Based Image Retrieval Systems. IEEE Computer Magazine, September 1995, pp.18–21.
P. J. B. Hancock, R. J. Bradley and L. S. Smith: The Principal Components of Natural Images. Network, 1992, 3:61–70.
J. J. Koenderink, and A. J. van Doorn: Representation of Local Geometry in the Visual System. Biological Cybernetics, 1987, vol. 55, pp. 367–375.
Tony Lindeberg: Scale-Space Theory in Computer Vision. Kluwer Academic Publishers, 1994, ISBN 0-7923-9418-6, Dordrecht, The Netherlands.
R. Manmatha: Measuring Affine Transformations Using Gaussian Filters. Proc. European Conference on Computer Vision, 1994, vol II, pp. 159–164.
R. Manmatha and J. Oliensis: Measuring Affine Transform — I, Scale and Rotation. Proc. DARPA IUW, 1993, pp. 449–458, Washington D.C.
Rajiv Mehrotra and James E. Gary: Similar-Shape Retrieval In Shape Data Management.IEEE Computer Magazine, September 1995, pp. 57–62.
A. Pentland, R. W. Picard, and S. Sclaroff: Photobook: Tools for Content-Based Manipulation of Databases. Proc. Storage and Retrieval for Image and Video Databases II, 1994, Vol.2, 185, SPIE, pp. 34–47, Bellingham, Wash.
R. Rao, and D. Ballard: Object Indexing Using an Iconic Sparse Distributed Memory. Proc. International Conference on Computer Vision, 1995, pp. 24–31.
S. Ravela, R. Manmatha and E. M. Riseman: Retrieval from Image Databases Using Scale-Space Matching. Technical Report UM-CS-95-104, 1995, Dept. of Computer Science, Amherst, MA 01003.
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 1996 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Ravela, S., Manmatha, R., Riseman, E.M. (1996). Image retrieval using scale-space matching. In: Buxton, B., Cipolla, R. (eds) Computer Vision — ECCV '96. ECCV 1996. Lecture Notes in Computer Science, vol 1064. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0015543
Download citation
DOI: https://doi.org/10.1007/BFb0015543
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-61122-6
Online ISBN: 978-3-540-49949-7
eBook Packages: Springer Book Archive