Image Segmentation Method for Rail Track Obstacle Based on Improved Fast Binarization
DOI: 10.23977/jipta.2016.11005 | Downloads: 67 | Views: 3763
Xu Tiantian 1, Li Jiying 1
1 School of Electronic & Information Engineering, Lanzhou Jiao tong University, Lanzhou, 730070, China
Corresponding AuthorXu Tiantian
The idea of recursion and limited range is introduced in the traditional fast binarization algorithm. Firstly, according to the characteristics of the fast binarization algorithm, the recursion formulas of four parameters are deduced, and the complexity of the image is calculated . Then fast threshold segmentation of image is finished within the reduced gray level range. Because of considering the four parameters formula of recursive and fully aware of the images complexity, the gray value of the image to be traversed is greatly reduced, and the redundancy of the algorithm is reduced. Finally, the improved algorithm is applied to extraction of railway track obstacle. The experimental results show that this algorithm complexity is lower than traditional algorithm and Otsu, and the computation speed can be improved by about 60%. It can meet the real-time requirement for railway track obstacle image segmentation, and the segmentation effect is almost the same as the traditional one.
KEYWORDSImage segmentation; Fast binarization algorithm; Image complexity; Railway track obstacle
CITE THIS PAPER
Jiying, L. and Tiantian X. (2016) Image Segmentation Method for Rail Track Obstacle Based on Improved Fast Binarization. Journal of Image Processing Theory and Applications (2016) 1: 21-26.
 WU Xu,HU Si-ji,CUI Yan-ping et.Study on Information Safeguard System of High-speed Railway[J].China Safety Science Journal,2005, 15(4):80-83.
 Song Juan. Research on Obstacle Detection for Railway Auto-detection System[D].thesis. Hangzhou: Zhejiang University,2008.
 Li Shengjin. Design and implementation of a video-based Railway level crossing obstacle detection algorithm [D]. Thesis. Shenyang: Shenyang Institute of Computing Technology, Chinese Academy of Sciences, 2012.
 LijuDong,Ge Yu. An optimization-based approach to image binarization [J]. SMC, 2004(4):3057-3062.
 Mehmet Sezgin,Bulent Sankur,Survey over image thresholding techniques and quantitative performance evaluation[J].Journal of Electronic Imaging.2004.13(1):146-165.
 Wu Yiquan,Meng Tianliang,Wu Shihua.Research Progress of Image Thresholding Methods in Recent 20 Years (1994-2014)[J]Journal Data Acquisition and Processing,2015.30(1):1-23.
 CHEN Zheng,SHI Yong-peng,JI Shupeng. Improved image threshold segmentation algorithm based on Otsu method [J].LASER & INFRARED,2012.42(5):584-588.
 DONG Zhong-yan,JIANG Li-xing,WANG Jun-ya et.Modified One-dimensional Otsu Algorithm Based on Image Complexity[J].Computer Science, 2015.42(6A):(171-174).
 GAO Zhen-yu,YANG Xiao-mei,GONG Jian-ming,JIN Hai.Research on Image Complexity Description Methods[J].Journal of Image and Graphics, 2010.15(1):129-135.