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
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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