Otsu thresholding segmentation algorithm based on Markov Random Field

Abstract

Since Otsu algorithm does not take the image spatial neighbor information into consideration, we combine the Markov random field with Otsu algorithm to integrate gray level information and spatial correlation information for the pixels. In this paper, Otsu thresholding algorithm based on Markov Random Field is proposed. In this algorithm, the neighborhood rejectability function is imported to Otsu algorithm and an threshold selection function is improved. The experiment results verify that applying our algorithm to road image segmentation can achieve good effects. Keywords-Image segmentation; Otsu algorithm; Markov Random Field(MRF); Neighborhood rejectability function; Road image

DOI: 10.1109/ICNC.2011.6022194

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Cite this paper

@inproceedings{Wang2011OtsuTS, title={Otsu thresholding segmentation algorithm based on Markov Random Field}, author={Qian Wang and Hua Zhang and Qi Dong and Qingxiao Niu and Guangping Xu and Yanbing Xue}, booktitle={ICNC}, year={2011} }