A new image thresholding method based on Gaussian mixture model

Zhi Kai Huang, Kwok Wing Chau

Research output: Journal article publicationJournal articleAcademic researchpeer-review

195 Citations (Scopus)


In this paper, an efficient approach to search for the global threshold of image using Gaussian mixture model is proposed. Firstly, a gray-level histogram of an image is represented as a function of the frequencies of gray-level. Then to fit the Gaussian mixtures to the histogram of image, the expectation maximization (EM) algorithm is developed to estimate the number of Gaussian mixture of such histograms and their corresponding parameterization. Finally, the optimal threshold which is the average of these Gaussian mixture means is chosen. And the experimental results show that the new algorithm performs better.
Original languageEnglish
Pages (from-to)899-907
Number of pages9
JournalApplied Mathematics and Computation
Issue number2
Publication statusPublished - 15 Nov 2008


  • Histogram
  • Optimization
  • Thresholding

ASJC Scopus subject areas

  • Computational Mathematics
  • Applied Mathematics


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