New results on efficient optimal multilevel image thresholding

M. Luessi*, M. Eichmann, G. M. Schuster, Aggelos K Katsaggelos

*Corresponding author for this work

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

7 Scopus citations

Abstract

Image thresholding is one of the most common image processing operations, since almost all image processing schemes need some sort of separation of the pixels into different classes. In order to find the thresholds, almost all methods analyze the histogram of the image. In most cases, the optimal thresholds are found by either minimazing or maximazing an objective function, which depends on the positions of the thresholds. We identify two classes of objective functions for which the optimal thresholds can be found by algorithms with low time complexity. We show, that for example the method proposed by Otsu [1] and other well known methods have objective functions belonging to these classes. By implementing the algorithms in ANSI C and comparing their execution times, we can make a quantitative statement about their performance.

Original languageEnglish (US)
Title of host publication2006 IEEE International Conference on Image Processing, ICIP 2006 - Proceedings
Pages773-776
Number of pages4
DOIs
StatePublished - Dec 1 2006
Event2006 IEEE International Conference on Image Processing, ICIP 2006 - Atlanta, GA, United States
Duration: Oct 8 2006Oct 11 2006

Publication series

NameProceedings - International Conference on Image Processing, ICIP
ISSN (Print)1522-4880

Other

Other2006 IEEE International Conference on Image Processing, ICIP 2006
CountryUnited States
CityAtlanta, GA
Period10/8/0610/11/06

Keywords

  • Dynamic programming
  • Image segmentation

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition
  • Signal Processing

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