Statistical approach to image segmentation on a cylindrical surface

Carroll Johnson, Jesus 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
Place of PublicationPiscataway, NJ, United States
PublisherPubl by IEEE
Pages771-772
Number of pages2
ISBN (Print)7800030393
StatePublished - 1988
Externally publishedYes
EventProceedings of the 1988 International Conference on Systems, Man, and Cybernetics - Beijing/Shenyang, China
Duration: Aug 8 1988Aug 12 1988

Other

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

Fingerprint

Image segmentation
Decision theory
Computer vision
Lighting
Processing

ASJC Scopus subject areas

  • Engineering(all)

Cite this

Johnson, C., Villalobos, J., 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). Piscataway, NJ, United States: Publ by IEEE.

Statistical approach to image segmentation on a cylindrical surface. / Johnson, Carroll; Villalobos, Jesus; Man, Xuan; Parra, Ramon.

Proc 1988 Int Conf Syst Man Cybern. Piscataway, NJ, United States : Publ by IEEE, 1988. p. 771-772.

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

Johnson, C, Villalobos, J, Man, X & Parra, R 1988, Statistical approach to image segmentation on a cylindrical surface. in Proc 1988 Int Conf Syst Man Cybern. Publ by IEEE, Piscataway, NJ, United States, pp. 771-772, Proceedings of the 1988 International Conference on Systems, Man, and Cybernetics, Beijing/Shenyang, China, 8/8/88.
Johnson C, Villalobos J, Man X, Parra R. Statistical approach to image segmentation on a cylindrical surface. In Proc 1988 Int Conf Syst Man Cybern. Piscataway, NJ, United States: Publ by IEEE. 1988. p. 771-772
Johnson, Carroll ; Villalobos, Jesus ; Man, Xuan ; Parra, Ramon. / Statistical approach to image segmentation on a cylindrical surface. Proc 1988 Int Conf Syst Man Cybern. Piscataway, NJ, United States : Publ by IEEE, 1988. pp. 771-772
@inproceedings{b2a0ece23bd6445cb9bf8e7c4db473d0,
title = "Statistical approach to image segmentation on a cylindrical surface",
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.",
author = "Carroll Johnson and Jesus Villalobos and Xuan Man and Ramon Parra",
year = "1988",
language = "English (US)",
isbn = "7800030393",
pages = "771--772",
booktitle = "Proc 1988 Int Conf Syst Man Cybern",
publisher = "Publ by IEEE",

}

TY - GEN

T1 - Statistical approach to image segmentation on a cylindrical surface

AU - Johnson, Carroll

AU - Villalobos, Jesus

AU - Man, Xuan

AU - Parra, Ramon

PY - 1988

Y1 - 1988

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=0024180193&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0024180193&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:0024180193

SN - 7800030393

SP - 771

EP - 772

BT - Proc 1988 Int Conf Syst Man Cybern

PB - Publ by IEEE

CY - Piscataway, NJ, United States

ER -