The week's pick
Random Articles
Reseach Article
Detection of Obstacles using Stereo Imaging
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 131 - Number 14 |
| Year of Publication: 2015 |
| Authors: Sai P. Deshmukh, A.M. Deshpande |
10.5120/ijca2015907556
|
Sai P. Deshmukh, A.M. Deshpande . Detection of Obstacles using Stereo Imaging. International Journal of Computer Applications. 131, 14 ( December 2015), 37-42. DOI=10.5120/ijca2015907556
Abstract
This paper presents an implementation of algorithm for detecting obstacles based on stereo vision technique. This algorithm mainly focuses on detection of obstacle and computation of obstacle depth based on stereo matching and disparity map. This technique incorporates several steps such as pre-processing and depth analysis for obstacle detection. In the preprocessing step, Otsu’s thresholding and adaptive thresholding methods are used for efficient detection of obstacles. After computation of obstacles, depth analysis is performed with the help of disparity map. Experimental results are demonstrated giving robust analysis of obstacle detection based on standard stereo dataset.
References
- Forsyth A. and Ponce J., Computer Vision: A modern approach, New Jersey, Prentice-Hall, 2002.
- S. Fazli, H. M. Dehnavi, P. Moallem, “A Robust detection Method in Highly Textured Environments using Stereo Vision”, Second International Conference on Machine Vision, IEEE Computer Society, pp. 97-100, Dec. 2009.
- Paulo Costa, Hugo Fernandes, Paulo Martins, João Barroso, “Obstacle detection using stereo imaging to assist the navigation of visually impaired people”, Procedia Computer Science, 14(2012) 83-93, ELSEVIER Science, 2012.
- Mu-Chun Su, Yi-Zeng Hsieh, and Yu-Xiang Zhao, “A Simple Approach to Stereo Matching and Its Application in Developing a Travel Aid for the Blind”, in Proceedings of the 2006 Joint Conference on Information Sciences, Department of Computer Science & Information Engineering, National Central University, Taiwan, R.O.C.
- G. Balakrishnan, G. Sainarayanan, R. Nagarajan, Sazali Yaacob, “Stereopsis Method for Visually Impaired to Identify Obstacles Based on Distance”, Third IEEE International Conference on Image and Graphics, pp. 580-583, Dec. 2004.
- J.C.A. Fernandes, M.J.O. Ferreira and J.A.B.C. Neves, “Fast Correction of Lens Distortion for Image Applications”, in Proceedings of the IEEE International Symposium on Industrial Electronics, ISIE’97, pp. 708 – 712, vol.2, July 1997.
- Radu Danescu, Cosmin Pantilie, Florin Oniga, and Sergiu Nedevschi, “Particle Grid Tracking System Stereo-vision Based Obstacle Perception in Driving Environments”, IEEE Intelligent Transportation Systems Magazine, Vol. 4, Issue 1, pp. 6-20, 2012.
- Kowalik, R., Kwasniewski, S., “Navigator - A Talking GPS Receiver for the Blind”, Lecture Notes in Computer Science 3118, pp. 446-449, Springer Berlin / Heidelberg (2004)
- Syedur Rahman, “Obstacle Detection for Mobile Robots Using Computer Vision”, Final Project, March 2005.
- http://homepages.inf.ed.ac.uk/rbf/HIPR2/adpthrsh.htm
- Shivani Thakur, Virender Sharma and Amit Chhabra, “A Review: Obstacle Tracking Using Image Segmentation’, International Journal of Innovative Research in Computer and Communication Engineering, vol. 2, no. 6, pp. 4590-4596, June 2014.
- Miss. Hetal J. Vala, Prof. Astha Baxi, A Review on Otsu Image Segmentation Algorithm, International Journal of Advanced Research in Computer Engineering & Technology (IJARCET) Volume 2, Issue 2, February 2013.
- Nobuyuki Otsu, “A Threshold Selection Method from Gray-Level Histograms”, IEEE Transactions On Systems, Man, And Cybernetics, Vol. Smc-9, No. 1, January 1979.
- P. Foggia, Jean-Michel Jolion, A. Limongiello, M. Vento, “Stereo Vision for Obstacle Detection: A Graph-Based Approach”, Graph-Based Representations in Pattern Recognition 2007, LNCS 4583, pp. 37-48.
- https://siddhantahuja.wordpress.com/tag/sum-of-absolute-differences-sad/
- http://cat.middlebury.edu/stereo/data.html
Index Terms
Keywords