Feature-based approach for image retrieval by sketch

Yin Chans; Zhibin Lei; Daniel P. Lopresti; Sun-Yuan Kung

doi:10.1117/12.290343

6 October 1997 Feature-based approach for image retrieval by sketch

Yin Chans, Zhibin Lei, Daniel P. Lopresti, Sun-Yuan Kung

Proceedings Volume 3229, Multimedia Storage and Archiving Systems II; (1997) https://doi.org/10.1117/12.290343
Event: Voice, Video, and Data Communications, 1997, Dallas, TX, United States

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. 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.

Citation Download Citation

Yin Chans, Zhibin Lei, Daniel P. Lopresti, and Sun-Yuan Kung "Feature-based approach for image retrieval by sketch", Proc. SPIE 3229, Multimedia Storage and Archiving Systems II, (6 October 1997); https://doi.org/10.1117/12.290343

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