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Reseach Article

A Novel Algorithm for Railway Tracks Detection using Satellite Imagery

by Muazzam Maqsood, Ali Javed, Nadeem Majeed
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 64 - Number 14
Year of Publication: 2013
Authors: Muazzam Maqsood, Ali Javed, Nadeem Majeed
10.5120/10700-4661

Muazzam Maqsood, Ali Javed, Nadeem Majeed . A Novel Algorithm for Railway Tracks Detection using Satellite Imagery. International Journal of Computer Applications. 64, 14 ( February 2013), 13-17. DOI=10.5120/10700-4661

@article{ 10.5120/10700-4661,
author = { Muazzam Maqsood, Ali Javed, Nadeem Majeed },
title = { A Novel Algorithm for Railway Tracks Detection using Satellite Imagery },
journal = { International Journal of Computer Applications },
issue_date = { February 2013 },
volume = { 64 },
number = { 14 },
month = { February },
year = { 2013 },
issn = { 0975-8887 },
pages = { 13-17 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume64/number14/10700-4661/ },
doi = { 10.5120/10700-4661 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:16:24.735507+05:30
%A Muazzam Maqsood
%A Ali Javed
%A Nadeem Majeed
%T A Novel Algorithm for Railway Tracks Detection using Satellite Imagery
%J International Journal of Computer Applications
%@ 0975-8887
%V 64
%N 14
%P 13-17
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Image processing applications have their wide ranged importance in today's world. Railway track detection is one of the hot research areas in visioning systems. An efficient algorithm and high quality images of railway tracks are required for accomplishing the desired task. Images produced by Google maps and Google earth are generally not so extraordinary. Their degraded quality affects the results of detection process. Images will be processed through railway detection algorithms and in the end results are compared with the low quality images in the context of someparameters such as accuracy. Also, the developed algorithm can be included in Geographic information System, so that it can be a base algorithm for other researchers to work on.

References
  1. Li Cheng; Minglun Gong; Schuurmans, D, Caelli, T. ; "Real-Time Discriminative Background Subtraction Image Processing'', IEEE Transactions, pp. 1401 – 1414, May 2011.
  2. Bi, Xiao-jun , Wang, Ting , "Adaptive Blind Image Restoration Algorithm of Degraded Image" Image and Signal Processing, 2008. CISP '08. Congress, pp. 536 – 540, 27-30 May 2008.
  3. Sathya, P. D. , Kayalvizhi, R, "Image segmentation using minimum cross entropy and bacterial foraging optimization algorithm Emerging Trends in Electrical and Computer Technology (ICETECT)", 2011 International Conference, pp. 500 – 506, 23-24 March 2011.
  4. Pi Youguo , Shu Huailin ; Liang Tiancai ," The Frame of Cognitive Pattern Recognition " Control Conference, 2007. CCC 2007. Chinese, pp. 694 – 696, July 26 2007-June 31 2007.
  5. Alipoor, M. , Ebrahimi, Z. ; Haddadnia, J. , "A novel logarithmic edge detection algorithm ", Machine Vision and Image Processing (MVIP), 2010 6th Iranian, pp. 1 – 6, 27-28 Oct. 2010.
  6. Xin Chen , Houjin Chen , "A novel color edge detection algorithm in RGB color space", Signal Processing (ICSP), 2010 IEEE 10th International Conference, pp. 793 – 796, 24-28 Oct. 2010.
  7. Huili Zhao , Guofeng Qin ; Xingjian Wang, "Improvement of canny algorithm based on pavement edge detection", Image and Signal Processing (CISP), 2010 3rd International Congress, pp. 964 – 967, 16-18 Oct. 2010.
  8. Mastorakis, G. , Davies, E. R. , "Improved line detection algorithm for locating road lane markings", Electronics Letters, pp. 183 – 184, February 3 2011.
  9. Xiaochuan Zhao , Peizhi Liu ; Min Zhang ; Xinxin Zhao , "A novel line detection algorithm in images based on improved Hough Transform and wavelet lifting transform", Information Theory and Information Security (ICITIS), 2010 IEEE International Conference, pp. 767 – 771, 17-19 Dec. 2010.
  10. Fontanelli, D. , Cappelletti, M. ; Macii, D. , "A RANSAC-based fast road line detection algorithm for high-speed wheeled vehicles", Instrumentation and Measurement Technology Conference (I2MTC), 2011 IEEE, pp. 1 – 6, 10-12 May 2011.
  11. Ali Javed, Khurram Ashfaq Qazi, Muazzam Maqsood, Khurram Ali Shah, " Efficient Algorithm for Railway Tracks Detection for Satellite Imagery" published in International Journal of Image, Graphics and Signal Processing, Vol. 4 No. 11 pp 34-40 October 2012.
  12. Ross, R. ," Track and turnout detection in video-signals using probabilistic spline curves" Intelligent Transportation Systems (ITSC), 2012 15th International IEEE Conference on, pp. 294 – 299, 16-19 Sept. 2012.
  13. Jenita Subash, "automatic road extraction from satellite images using extended kalman filtering and efficient particle filtering".
  14. Movaghati, S. ; Moghaddamjoo, A. ; Tavakoli, A. ; "Road Extraction From Satellite Images Using Particle Filtering and Extended Kalman Filtering Geoscience and Remote Sensing", IEEE Transactions, pp. 2807 – 2817, July 2010.
  15. Zu Whan Kim , Huertas, A. ; Nevatia, R. , "Automatic description of complex buildings with multiple images", Applications of Computer Vision, 2000, Fifth IEEE Workshop on. , pp. 155 – 162.
  16. Fatih Kaleli and Yusuf Sinan Akgul, "Vision-Based Railroad Track ExtractionUsing Dynamic Programming" GIT Vision Lab, http://vision. gyte. edu. tr/.
  17. Shivanand, T. ; Rahman, S. ; Pillai, G, "Efficien androbust detection and recognition of objects in grayscale images Computational Intelligence and Computing Research (ICCIC)", 2010 IEEE International Conference, pp. 1 – 6, 28-29 Dec. 2010.
Index Terms

Computer Science
Information Sciences

Keywords

Accuracy catastrophe Context locomotive