NDLI: Geometric-similarity retrieval in large image bases

Content Provider	IEEE Xplore Digital Library
Author	Fudos, I. Palios, L. Pitoura, E.
Copyright Year	2002
Description	Author affiliation: Dept. of Comput. Sci., Ioannina Univ., Greece (Fudos, I.)
Abstract	We propose a novel approach to shape-based image retrieval that builds upon a similarity criterion which is based on the average point set distance. Compared to traditional techniques, such as dimensionality reduction, our method exhibits better behavior in that it maintains the average topology of shapes independently of the number of points used to represent them and is more resilient to noise. An efficient algorithm is presented based on an incremental "fattening," of the query shape until the best match is discovered. The algorithm uses simplex range search techniques and fractional cascading to provide an average polylogarithmic time complexity on the total number of shape vertices. The algorithm is extended to perform additional fast approximate matching, when there is no image sufficiently similar to the query image. We present techniques for the efficient external storage of the shape base and of the auxiliary geometric data structures used by the algorithm. Finally, we show how our approach can be used for processing queries, containing pairwise relations of object boundaries such as contain, tangent, and overlap. Such queries are either extracted from some user drafted sketch or defined explicitly by the user. Alternative methods are presented for forming query execution plans.
Sponsorship	IEEE Comput. Soc. Tech. Committee on Data Eng.
Starting Page	441
Ending Page	450
File Size	452462
Page Count	10
File Format	PDF
ISBN	0769515312
ISSN	10636382
DOI	10.1109/ICDE.2002.994757
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2002-02-26
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image retrieval Shape Multi-stage noise shaping Phase noise Computer science Topology Noise reduction 1f noise Noise shaping Data structures
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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