Abstract
The rate of road accidents is increasing day by day that causes death throughout the year. Overspeed of the vehicle is one of the main reasons for these accidents. With this view, speed detection of a vehicle is very important to control this severe problem. This paper describes a TensorFlow machine learning library API-based method to estimate the speed of a vehicle from video images to find either it crossed the speed limit or not. The effectiveness of this technique is confirmed through experimentation.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Tribune D (2018) saw surge in road accidents. https://www.dhakatribune.com/bangladesh/nation/2019/01/16/2018-saw-surge-in-road-accidents
Sivaraman S, Manubhai Trivedi M (2013) Looking at vehicles on the road: a survey of vision-based vehicle detection, tracking, and behavior analysis. IEEE transactions on intelligent transportation systems, vol 14, no 4, December 2013, pp 1773–1795
Ushakiranmai M, Sai Thirumal G (2015) Design Portable sensors system for vehicle counting, classification, and speed measurement in traffic junctions. Int J Prof Eng Stud V(5):174–179
Shedbalkar K, Dhamangaonkar AP, Walchand ABP (2012) Speed estimation using extended Kalman filter for PMSM. In: 2012 international conference on emerging trends in electrical engineering and energy management (ICETEEEM), Chennai, India, 13–15 December 2012, pp 433–435, IEEE Explore
Penchas B, Bell T, Monteiro M (2019) A deep learning approach to vehicle speed estimation. http://cs229.stanford.edu/proj2017/final-reports/5244226.pdf. Accessed 30 July 2019
Awni Abbass A (2010) Estimating vehicle speed using image processing. AL-Mansour J 14:127–141
Gholami Rad A, Dehghani A, Rehan Karim M (2010) Vehicle speed detection in video image sequences using CVS method. Int J Physical Sci 5(17)–2555–2563
Setiyono B, Ratna Sulistyaningrum D, Soetrisno, Fajriyah F, Wahyu Wicaksono D. Vehicle speed detection based on Gaussian mixture model using sequential of images. J Phys: Conf Ser 890(1):012144. IOP Publishing. https://iopscience.iop.org/article/10.1088/1742-6596/890/1/012144/pdf
Reduanul Haque M, Golam Moazzam Md, Islam S, Das R, Shorif Uddin M (2016) Vehicle speed determination from video streams using image processing. In: International workshop on computational intelligence (IWCI), 12–13 December 2016, Dhaka, Bangladesh, pp 252–255, (IEEE Explore)
Francis J (2019) Object detection with tensor flow. https://www.oreilly.com/ideas/object-detection-with-tensorflow. Accessed 30 July 2019
Liu W, Anguelov D, Erhan D, Szegedy C, Reed S, Fu C-Y, Berg AC (2016) SSD: single shot multi box detector. ECCV 2016, Amsterdam, Netherlands, October 11–14, 2016, Lecture Notes in Computer Science, vol 9905, Springer, pp 21–37, 2016
A Graphical Image Annotation Tool—“LabelImg,”. https://github.com/tzutalin/labelImg
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Akter, M., Ferdous, J., Eva, M.N., Shorif, S.B., Fahmida Islam, S., Uddin, M.S. (2021). Vehicle Detection and Its Speed Measurement. In: Shorif Uddin, M., Sharma, A., Agarwal, K.L., Saraswat, M. (eds) Intelligent Energy Management Technologies. Algorithms for Intelligent Systems. Springer, Singapore. https://doi.org/10.1007/978-981-15-8820-4_9
Download citation
DOI: https://doi.org/10.1007/978-981-15-8820-4_9
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-15-8819-8
Online ISBN: 978-981-15-8820-4
eBook Packages: EngineeringEngineering (R0)