Title :
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
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;
Conference_Titel :
Natural Computation (ICNC), 2011 Seventh International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-9950-2
DOI :
10.1109/ICNC.2011.6022194