A feature-based approach for image retrieval by sketch

Yin Chans, Zhibin Lei, Daniel Lopresti, S. Y. Kung

Research output: Contribution to journalConference article

14 Scopus citations

Abstract

In this paper, we introduce a feature-based approach for image retrieval by sketch. Using edge segments as features which are modeled by implicit polynomials(IPs), we hope to provide a similarity computation method that is robust towards user query sketch distortions. We report some preliminary results of the first phase of our work in this paper. From these results, we could see that the feature-based method, which currently uses edge features modeled by first degree IPs, generally performs better than a pixel-based method that has been adopted by a number of well-known content-based image indexing and retrieval systems such as the IBM QBIC project.2 The feature-based method appears more robust and tolerant towards distortions in query sketches. We attribute this quality to the fact that it uses more structural information to compute the similarities between images. We will also describe a prototype built upon the Java technology that allows queries over the WWW. Finally we will discuss the promise and limitations of the feature-based method and conclude the paper with a look at areas for future work.

Original languageEnglish (US)
Pages (from-to)220-231
Number of pages12
JournalProceedings of SPIE - The International Society for Optical Engineering
Volume3229
DOIs
StatePublished - Dec 1 1997
EventMultimedia Storage and Archiving Systems II - Dallas, TX, United States
Duration: Nov 3 1997Nov 3 1997

All Science Journal Classification (ASJC) codes

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

Keywords

  • Content-based
  • Image retrieval
  • Implicit polynomial

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