Statistical approach to image segmentation on a cylindrical surface

Carroll Johnson, Rene Villalobos, Xuan Man, Ramon Parra

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

Abstract

The authors discuss the development of a machine vision system using Bayesian decision theory to classify target and nontarget areas on a cylindrical surface. Algorithms developed using Bayesian theory are used to extract a cylindrical surface from a textured background and then to segment the image into target and nontarget areas for subsequent processing. The advantages of the algorithms are that no a priori grey-level threshold values are required, illumination constraints are reduced, and the results are consistent.

Original languageEnglish (US)
Title of host publicationProc 1988 Int Conf Syst Man Cybern
PublisherPubl by IEEE
Pages771-772
Number of pages2
ISBN (Print)7800030393
StatePublished - Dec 1 1988
Externally publishedYes
EventProceedings of the 1988 International Conference on Systems, Man, and Cybernetics - Beijing/Shenyang, China
Duration: Aug 8 1988Aug 12 1988

Publication series

NameProc 1988 Int Conf Syst Man Cybern

Other

OtherProceedings of the 1988 International Conference on Systems, Man, and Cybernetics
CityBeijing/Shenyang, China
Period8/8/888/12/88

ASJC Scopus subject areas

  • Engineering(all)

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  • Cite this

    Johnson, C., Villalobos, R., Man, X., & Parra, R. (1988). Statistical approach to image segmentation on a cylindrical surface. In Proc 1988 Int Conf Syst Man Cybern (pp. 771-772). (Proc 1988 Int Conf Syst Man Cybern). Publ by IEEE.