Segmentation of color image using deterministic annealing EM

We present a color image segmentation algorithm based on statistical models. A novel deterministic annealing EM (expectation maximisation) formula is used to estimate the parameters of the Gaussian mixture model which represents the muti-colored objects statistically. The experimental results show t...

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Bibliographic Details
Published inProceedings 15th International Conference on Pattern Recognition. ICPR-2000 Vol. 3; pp. 642 - 645 vol.3
Main Authors Wan Hyun Cho, Soon Young Park, Jong Hyun Park
Format Conference Proceeding
LanguageEnglish
Published IEEE 2000
Subjects
Annealing
Clustering algorithms
Color
Entropy
Image segmentation
Maximum likelihood estimation
Parameter estimation
Probability distribution
Robot sensing systems
Statistics
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Summary:We present a color image segmentation algorithm based on statistical models. A novel deterministic annealing EM (expectation maximisation) formula is used to estimate the parameters of the Gaussian mixture model which represents the muti-colored objects statistically. The experimental results show that the proposed deterministic annealing EM provides a global optimal solution for the maximum likelihood parameter estimation and the image field is segmented efficiently by using the estimates.
ISBN:0769507506
9780769507507
ISSN:1051-4651
2831-7475
DOI:10.1109/ICPR.2000.903627