Vehicle Counting using Video Image Processing  
  Authors : Megha C. Narhe; Dr.M.S.Nagmode


It is important to know the road traffic density especially in mega cities for effective traffic management and intelligent transportation system (ITS). In recent years, video monitoring have been widely used in intelligent transportation system (ITS). As one of the important research topic in video monitoring based intelligent transportation system (ITS) is vehicle classification and counting. Vehicle classification and counting is challenging task due to problems like motion blurs, varying image resolution etc. So far numerous algorithms have been developed for vehicle classification and counting. This paper proposes an effective Scale Invariant Feature transform (SIFT) algorithm used for moving vehicle classification and after classification counting will be done according to the class. This will help to improve efficiency and reliability of vehicle classification and counting technique.


Published In : IJCAT Journal Volume 1, Issue 7

Date of Publication : 31 August 2014

Pages : 358 - 362

Figures :06

Tables : --

Publication Link : Vehicle Counting using Video Image Processing




Megha C. Narhe : Department of Electronics& Telecommunication, Pune University, MIT College of Engineering Pune, Maharashtra, India

Dr.M.S.Nagmode : Department of Electronics& Telecommunication, Pune University, MIT College of Engineering Pune, Maharashtra, India








Vehicle classification and counting


In this paper Scale Invariant Feature Transform (SIFT) is used for vehicle classification and counting is done according to class of vehicle is described. In this paper keypoint detection , feature matching and classification is done using Matlab R2013a. With the help of SIFT algorithm, extraction invariant image features, that are stable over image translation, rotation, scaling, camera viewpoint and somewhat invariant to changes in the illumination will be possible.










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