Skip to main content
Disciplines
Automotive Business IT + Informatics Construction + Real Estate Electrical Engineering + Electronics Energy + Sustainability Insurance + Risk Finance + Banking Management + Leadership Marketing + Sales Mechanical Engineering + Materials
Events
DE
EN
Books
Journals
Topic Page
Marketing
Start single access now
Access for companies
EXTENDED SEARCH
Log in
Top
Published in:
Pharmacophore Modeling and Docking Studies of SNCA Receptor with Some Active Phytocompounds from Selected Ayurvedic Medicinal Plants Known for their CNS Activity Read chapter Read first chapter

2018 | OriginalPaper | Chapter

A Two-Stage Detection Approach for Car Counting in Day and Nighttime

Authors : Van-Huy Pham, Duc-Hau Le

Published in: Information Systems Design and Intelligent Applications

Publisher: Springer Singapore

Log in

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

We developed a car counting system using car detection methods for both daytime and nighttime traffic scenes. The detection methods comprise two stages: car hypothesis generation and hypothesis verification. For daytime traffic scenes, we proposed a new car hypothesis generation by rapidly locating car windshield regions, which are used to estimate car positions in occlusion situations. For car hypothesis at nighttime, we proposed an approach using k-means clustering-based segmentation to find headlight candidates to facilitate the later pairing process. Counting decision is made from Kalman filter-based tracking, followed by rule-based verification. The results evaluated on real-world traffic videos show that our system can work well in different conditions of lighting and occlusion.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

inform now
previous chapter A Modification of Solution Optimization in Support Vector Machine Simplification for Classification
next chapter An Effective FP-Tree-Based Movie Recommender System
Literature
1.
Bin, T., Qingming, Y., Yuan, G., Kunfeng, W., Ye, L.: Video processing techniques for traffic flow monitoring: A survey. In: Intelligent Transportation Systems (ITSC), 14th International IEEE Conference on, pp. 1103–1108. (2011).
2.
Zielke, T., Brauckmann, M., Vonseelen, W.: Intensity and Edge-Based Symmetry Detection with an Application to Car-Following. Cvgip-Imag Understan 58, 177–190 (1993).
3.
Teoh, S.S., Braunl, T.: Symmetry-based monocular vehicle detection system. Machine Vision and Applications 23, 831–842 (2012).
4.
Luo-Wei, T., Hsieh, J.-W., Kao-Chin, F.: Vehicle detection using normalized color and edge map. In: IEEE International Conference on Image Processing, pp. II-598–601. (2005).
5.
Betke, M., Haritaoglu, E., Davis, L.S.: Real-time multiple vehicle detection and tracking from a moving vehicle. Machine Vision and Applications 12, 69–83 (2000).
6.
Tzomakas, C., Seelen, W.v.: Vehicle Detection in Traffic Scenes Using Shadows. (1998).
7.
Bucher, T., Curio, C., Edelbrunner, J., Igel, C., Kastrup, D., Leefken, I., Lorenz, G., Steinhage, A., von Seelen, W.: Image processing and behavior planning for intelligent vehicles. IEEE T Ind Electron 50, 62–75 (2003).
8.
Kuo, Y.C., Pai, N.S., Li, Y.F.: Vision-based vehicle detection for a driver assistance system. Comput Math Appl 61, 2096–2100 (2011).
9.
Stauffer, C., Grimson, W.E.L.: Adaptive background mixture models for real-time tracking. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 252. (2000).
10.
Boninsegna, M., Bozzoli, A.: A tunable algorithm to update a reference image. Signal Process-Image 16, 353–365 (2000).
11.
Tyrer, J.R., Lobo, L.M.: An optical method for automated roadside detection and counting of vehicle occupants. P I Mech Eng D-J Aut 222, 765–774 (2008).
12.
Buch, N., Velastin, S.A., Orwell, J.: A Review of Computer Vision Techniques for the Analysis of Urban Traffic. IEEE T Intell Transp 12, 920–939 (2011).
13.
Thou-Ho, C., Yu-Feng, L., Tsong-Yi, C.: Intelligent Vehicle Counting Method Based on Blob Analysis in Traffic Surveillance. In: International Conference on Innovative Computing, Information and Control, pp. 238–238. (2007).
14.
Ying-Li, T., Lu, M., Hampapur, A.: Robust and efficient foreground analysis for real-time video surveillance. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 1182–1187 vol. 1181. (2005).
15.
Dalal, N., Triggs, B.: Histograms of oriented gradients for human detection. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 886–893. (2005).
16.
Taktak, R., Dufaut, M., Husson, R.: Vehicle detection at night using image processing and pattern recognition. In: Image Processing.Proceedings. ICIP-94., IEEE International Conference, pp. 296–300 vol.292. (1994).
17.
Wang, J., Sun, X., Guo, J.: A region tracking-based vehicle detection algorithm in nighttime traffic scenes. Sensors 13, 16474–16493 (2013).
18.
Cucchiara, R., Piccardi, M., Mello, P.: Image analysis and rule-based reasoning for a traffic monitoring system. Intelligent Transportation Systems, IEEE Transactions, 119–130 (2000).
19.
Van Pham, H., Lee, B.-R.: Front-view car detection and counting with occlusion in dense traffic flow. Int. J. Control Autom. Syst. 13, 1150–1160 (2015).
20.
Canny, J.: A computational approach to edge detection. IEEE transactions on pattern analysis and machine intelligence 8, 679–698 (1986).
21.
Felzenszwalb, P.F., Girshick, R.B., McAllester, D., Ramanan, D.: Object detection with discriminatively trained part-based models. IEEE transactions on pattern analysis and machine intelligence 32, 1627–1645 (2010).
22.
Hoang, V.D., Le, M.H., Jo, K.H.: Hybrid cascade boosting machine using variant scale blocks based HOG features for pedestrian detection. Neurocomputing 135, 357–366 (2014).
Metadata
Title
A Two-Stage Detection Approach for Car Counting in Day and Nighttime
Authors
Van-Huy Pham
Duc-Hau Le
Copyright Year
2018
Publisher
Springer Singapore
Book
Information Systems Design and Intelligent Applications

Print ISBN: 978-981-10-7511-7

Electronic ISBN: 978-981-10-7512-4

Copyright Year: 2018

DOI
https://doi.org/10.1007/978-981-10-7512-4_16

Premium Partner

    Image Credits