Weighted voting-based robust image thresholding

Shahryar Rahnamayan, Hamid R. Tizhoosh, Magdy M.A. Salama

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


A new robust image thresholding technique is introduced in this paper. Comprehensive experiments show that a single thresholding method can not be successful for all kind of images. The proposed approach uses fusion of some well-known thresholding methods by applying weighted voting at the decision level. The main objective is improving robustness of thresholding approach by participating several methods. Although, the proposed approach can not guaranty the best result for all kind of images but it shows higher performance and consistent/smoother behavior in overall. The performance of the new approach and nine well-established thresholding methods are compared by applying to an image set with high image diversity. The comparison results show that the proposed approach outperforms other nine well-established thresholding approaches. The proposed approach has been explained in details and experimental results are provided.

Original languageEnglish (US)
Title of host publication2006 IEEE International Conference on Image Processing, ICIP 2006 - Proceedings
Number of pages4
StatePublished - 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


Other2006 IEEE International Conference on Image Processing, ICIP 2006
Country/TerritoryUnited States
CityAtlanta, GA


  • Fusion
  • Kittler
  • Misclassification error
  • Segmentation
  • Thresholding
  • Voting

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition
  • Signal Processing


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