Similar Shape Retrieval in MARS

Abstract

This paper presents a novel approach to representing 2-dimensional shapes that adaptively models different portions of the shape at different resolutions, having higher resolution where it improves the quality of the representation and lower resolution elsewhere. The proposed representation is invariant to scale, translation, and rotation. The representation is amenable to indexing using existing multidimensional index structures and can thus support efficient similarity retrieval. The experiments reported here show that the adaptive resolution technique performs significantly better compared to the fixed resolution approach previously proposed in the literature.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2000
Accession Number
ADA465881

Entities

People

  • Kaushik Chakrabarti
  • Kriengkrai Porkaew
  • Michael Ortega-binderberger
  • Peng Zuo
  • Sharad Mehrotra

Organizations

  • University of Illinois Urbana–Champaign

Tags

DTIC Thesaurus Topics

  • Accuracy
  • Algorithms
  • Computer Science
  • Databases
  • Decomposition
  • Digital Images
  • Education
  • Electronic Commerce
  • High Resolution
  • Images
  • Information Operations
  • Low Resolution
  • Military Research
  • Precision
  • Rotation
  • Sequences
  • Two Dimensional

Readers

  • Computational Fluid Dynamics (CFD)
  • Computational Linguistics
  • Regression Analysis.