Otsu thresholding segmentation algorithm based on Markov Random Field

Author

Qian Wang ; Hua Zhang ; Qi Dong ; Qingxiao Niu ; Guangping Xu ; Yanbing Xue

Author_Institution

Tianjin Key Lab. of Intell. Comput. & Novel Software Technol., Tianjin Univ. of Technol., Tianjin, China

Volume

2

fYear

2011

fDate

26-28 July 2011

Firstpage

969

Lastpage

972

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

Markov processes; image resolution; image segmentation; Markov random field; Otsu thresholding segmentation algorithm; gray level information; image spatial neighbor information; neighborhood rejectability function; road image segmentation; spatial correlation information; Algorithm design and analysis; Correlation; Image color analysis; Image segmentation; Markov random fields; Roads; Image segmentation; Markov Random Field (MRF); Neighborhood rejectability function; Otsu algorithm; Road image;

fLanguage

English

Publisher

ieee

Conference_Titel

Natural Computation (ICNC), 2011 Seventh International Conference on

Conference_Location

Shanghai

ISSN

2157-9555

Print_ISBN

978-1-4244-9950-2

Type

conf

DOI

10.1109/ICNC.2011.6022194

Filename

6022194