SHAPE MATCHING BY CORRELATING RELATIONAL MODELS.

Ho Soo Lee, Nitish V. Thakor

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper describes a new shape matching algorithm using the correlation of the relational models. Relational descriptions of shapes are incorporated in a correlation matching method. From relational decriptions of a shape, a list of relational spectrums for each feature is constructed, which preserves the global information of the whole shape. Shape matching of a candidate shape against the prototype model is performed by correlating the relational spectrums of the prototype and candidate models. Although the correlation technique is adopted in matching process, the proposed matching algorithm is invariant under elementary transformations such as translation, rotation, and scaling since the items being correlated are global relations among shape features.

Original languageEnglish (US)
Title of host publicationProceedings - International Conference on Pattern Recognition
PublisherIEEE
Pages1178-1181
Number of pages4
ISBN (Print)0818605456
StatePublished - Dec 1 1984
Externally publishedYes

Publication series

NameProceedings - International Conference on Pattern Recognition
Volume2

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition

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