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Research Article
Vehicle Detection and Speed Tracking System
Shashwat tripathi1
Vivek kumar Singh2
Shahzad ahmed3
Shivam srivastav4
Zainab Kamal Khan5
1234B. tech 4thYear, Dept. of Computer Science and Engineering, ITM Gorakhpur, UP, India. 5Assistant Professor, Dept. of Computer Science and engineering, ITM Gorakhpur, UP, India.
Published Online: May-June 2022
Pages: 162-166
Cite this article
No DOIReferences
1. O. Smirg, Z. Smekal, M. K. Dutta, and B. Kakani, “Automatic detection of the direction and speed of moving objectsin the video,” in 2013 Sixth International Conference on Contemporary Computing (IC3), pp. 86– 90, Aug 2013.
2. J. x. Wang, “Research of vehicle speed detection algorithm in video surveillance,” in 2016 International Conference on Audio, Language and Image Processing (ICALIP), pp. 349–352, July 2016.
3. C. Pornpanomchai and K. Kongkittisan, “Vehicle speed detection system,” in 2009 IEEE International Conference on Signal and Image
Processing Applications, pp. 135–139, Nov 2009.
4. M. A.Alavianmehr, A. Zahmatkesh, and A. Sodagaran, “A new vehicle detect method based on gaussian mixture model along with estimate moment velocity using optical flow,”
5. I. Iszaidy, A. Alias, R. Ngadiran, R. B. Ahmad, M. I. Jais, and D. Shuhaizar,“Video size comparison for embedded vehicle speed detection travel time estimation system by using raspberry pi,” in 2016 International Conference on Robotics, Automation and Sciences (ICORAS), pp.1–4, Nov 2016
6. K. V. K. Kumar, P. Chandrakant, S. Kumar, and K. J. Kushal, “Vehicle speed detection using cornerdetection,” in Proceedings of the
2014 Fifth International Conference on Signal and Image Processing, ICSIP ’14, (Washington, DC, USA), pp. 253– 258, IEEE Computer
Society, 2014.
7. H.-Y. Lin, K.-J. Li, and C.-H. Chang, “Vehicle speed detection from a single motion blurred image,” Image and Vision Computing,
vol. 26, no. 10, pp. 1327 –1337, 2008.
8. C. Stauffer and W. E. L. Grimson, “Adaptive background mixture models for real-time tracking,” in Computer Vision and Pattern
Recognition, 1999. IEEE Computer Society Conference on. vol. 2, pp. 246–252, IEEE, 1999.
9. A. Burton and J. Radford, Thinking in perspective: critical essays in the study of thought processes. Methuen, 1978.
10. D. H. Warren and E. R. Strelow, Electronic Spatial Sensing for the Blind: Contributions from Perception, Rehabilitation, and
Computer Vision, vol. 99. Springer Science & Business Media, 2013.
11. G. Bradski and A. Kaehler, Learning OpenCV: Computer vision with the OpenCV library. " O’Reilly Media, Inc.", 2008
2. J. x. Wang, “Research of vehicle speed detection algorithm in video surveillance,” in 2016 International Conference on Audio, Language and Image Processing (ICALIP), pp. 349–352, July 2016.
3. C. Pornpanomchai and K. Kongkittisan, “Vehicle speed detection system,” in 2009 IEEE International Conference on Signal and Image
Processing Applications, pp. 135–139, Nov 2009.
4. M. A.Alavianmehr, A. Zahmatkesh, and A. Sodagaran, “A new vehicle detect method based on gaussian mixture model along with estimate moment velocity using optical flow,”
5. I. Iszaidy, A. Alias, R. Ngadiran, R. B. Ahmad, M. I. Jais, and D. Shuhaizar,“Video size comparison for embedded vehicle speed detection travel time estimation system by using raspberry pi,” in 2016 International Conference on Robotics, Automation and Sciences (ICORAS), pp.1–4, Nov 2016
6. K. V. K. Kumar, P. Chandrakant, S. Kumar, and K. J. Kushal, “Vehicle speed detection using cornerdetection,” in Proceedings of the
2014 Fifth International Conference on Signal and Image Processing, ICSIP ’14, (Washington, DC, USA), pp. 253– 258, IEEE Computer
Society, 2014.
7. H.-Y. Lin, K.-J. Li, and C.-H. Chang, “Vehicle speed detection from a single motion blurred image,” Image and Vision Computing,
vol. 26, no. 10, pp. 1327 –1337, 2008.
8. C. Stauffer and W. E. L. Grimson, “Adaptive background mixture models for real-time tracking,” in Computer Vision and Pattern
Recognition, 1999. IEEE Computer Society Conference on. vol. 2, pp. 246–252, IEEE, 1999.
9. A. Burton and J. Radford, Thinking in perspective: critical essays in the study of thought processes. Methuen, 1978.
10. D. H. Warren and E. R. Strelow, Electronic Spatial Sensing for the Blind: Contributions from Perception, Rehabilitation, and
Computer Vision, vol. 99. Springer Science & Business Media, 2013.
11. G. Bradski and A. Kaehler, Learning OpenCV: Computer vision with the OpenCV library. " O’Reilly Media, Inc.", 2008
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