Browse > Article
http://dx.doi.org/10.9717/kmms.2015.18.3.287

Image-based Subway Security System by Histogram Projection Technology  

Bai, Zhiguo (Dept. of Smart Distribution Research Center, Korea Electrotechnology Research Institute)
Jung, Sung-Hwan (Dept. of Computer Engineering, Changwon National University)
Publication Information
Abstract
A railway security detection system is very important. There are many safety factors that directly affect the safe operation of trains. Security detection technology can be divided into passive and active approaches. In this paper, we will first survey the railway security systems and compare them. We will also propose a subway security detection system with computer vision technology, which can detect three kinds of problems: the spark problem, the obstacle problem, and the lost screw problem. The spark and obstacle detection methods are unique in our system. In our experiment using about 900 input test images, we obtained about a 99.8% performance in F- measure for the spark detection problem, and about 94.7% for the obstacle detection problem.
Keywords
Subway Security Detection; Computer Vision Technology; Spark Problem; Obstacle Problem; Lost Screw Problem;
Citations & Related Records
연도 인용수 순위
  • Reference
1 D.M. Li, “Intelligence Image Processing based Railway Obstacle Detection On-vehicle Technology,” Journal of Southwest Jiaotong University, Vol. 2, No. 4, pp. 12-19, 2007.
2 R. Passarella and B. Tutuk, “Design Concept of Train Obstacle Detection System in Indonesia,” International Journal of Research and Reviews in Applied Sciences, Vol. 9, Issue 3, pp. 20-27, 2011.
3 S. Mockel, F. Scherer, and P.F. Schuster, “Multi-sensor Obstacle Detection on Railway Tracks,” Proceeding of IEEE Intelligent Vehicles Symposium, Vol. 9, No. 11, pp. 42-46, 2003.
4 H. Möller, H. Möller, B. Hulin, W. Krötz, and B. Sarnes, “Video Based Obstacle Detection in Catenaries of Railways,” Proceeding of 6th International Conference on Pattern Recognition and Information Processing, Vol. 1, No. 7, pp. 275-287, 2001.
5 S.H. Jung and B.H.. Jo, “Line Detection in the Image of a Wireless Mobile Robot Using an Efficient Preprocessing and Improved Hough Transform,” Journal of Multimedia Information System, Vol. 14, No. 6, pp. 719-729, 2011.
6 S.H. Jung and M.H. Lee, Practical Digital Image Processing Using MATLAB, Hongrung Publishing Co., Seoul, 2005.
7 A. Carlson, D. Frincke, and M. Laude, “Railway Security Issues: A Survey of Developing Railway Technology,” Proceeding of International Conference on Computer, Communication, and Control Technologies, Vol. 1, No. 3, pp. 1-6, 2003.
8 C. Seyve, “Metro Railway Security Algorithms with Real World Experience Adapted to the RATP Dataset,” Proceeding of IEEE International Conference on Advanced Video and Signal Based Surveillance, Vol. 15, No. 16, pp. 177-182, 2005.
9 L. Tong and L. Zhu, “Railway Obstacle Detection Using Onboard Forward-Viewing Camera,” Journal of Transportation Systems Engineering and Information Technology, Vol. 12, No. 4, pp. 80-83, 2012.
10 S. Terakubo, M. Morii, and T. Kashihara, “Development of a Road Obstacle Sensor Combining Image Processing and a Laser Radar,” Proceeding of the 1998 IEEE International Conference on Intelligent Vehicles, Vol. 2, pp. 521-526, 1998.
11 W. Kato and T. Kawami, “Application of Image Processing Technology to Shinkansen Inspection Car,” Institute for Mathematics and Computer Science World Congress, Vol. 3, No. 21, pp. 1003-1009, 2005.