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Ozkurt, C. and Camci, F. (2009) Automatic Traffic Density Estimation and Vehicle Classification for Traffic Surveillance Systems Using Neural Networks. Mathematical and Computational Applications, 14, 187-196.

has been cited by the following article:

• TITLE: The Automated Vehicle Detection of Highway Traffic Images by Differential Morphological Profile

  AUTHORS: Bharti Sharma, Vinod Kumar Katiyar, Arvind Kumar Gupta, Akansha Singh

  KEYWORDS: Average Filter, Differential Morphology Closing Profile, Structure Element, Thresholding, Vehicle Detection

  JOURNAL NAME: Journal of Transportation Technologies, Vol.4 No.2, April 29, 2014

  ABSTRACT: Vehicle detection has been the critical part of the traffic surveillance system for many years. However, vehicle detection method is still challenging. In this paper, differential morphology closing profile is used to extract the vehicle automatically from the traffic image. Along with closing profile, some addition operation has been applied as a part of the algorithm to get the high detection and quality rate. Result demonstrated that the novel method has an excellent detection and quality percentage. We also have compared our automated detection method with other traditional image processing based methods and the results indicate that our proposed method provides better results than traditional image processing based methods.