Image segmentation based on scaled fuzzy membership functions

Jan Jantzen, P. Ring,, Pernille Christiansen

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

368 Downloads (Pure)


As a basis for an automated interpretation of magnetic resonance images, the authors propose a fuzzy segmentation method. The method uses five standard fuzzy membership functions: small, small medium, medium, large medium, and large. The method fits these membership functions to the modes of interest in the image histogram by means of a piecewise-linear transformation. A test example is given concerning a human head image, including a sensitivity analysis based on the fuzzy area measure. The method provides a rule-based interface to the physician
Original languageEnglish
Title of host publicationProceedings of the 2nd IEEE International Conference on Fuzzy Systems
VolumeVolume 2
Publication date1993
ISBN (Print)07-80-30614-7
Publication statusPublished - 1993
EventIEEE International Conference on Fuzzy Systems - San Francisco, CA
Duration: 1 Jan 1993 → …
Conference number: 2nd


ConferenceIEEE International Conference on Fuzzy Systems
CitySan Francisco, CA
Period01/01/1993 → …

Bibliographical note

Copyright 1993 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.


Dive into the research topics of 'Image segmentation based on scaled fuzzy membership functions'. Together they form a unique fingerprint.

Cite this