International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

Monthly Journal for Science , Computer Science and Engineering

Volume5,March 2018,

Topic : A Survey on Vehicle Classification Techniques

Authors:G.Sundaravalli || K.Krishnaveni

Abstract:Vehicle classification has emerged as a significant field of study because of its importance in the variety of applications like surveillance, security system, traffic congestion, avoidance, accident prevention etc. So far numerous algorithms have been implemented for classifying vehicles; the aim of this paper is to give the opportunity to the researcher to become closely familiar with the methods used for classification of vehicles. Methods based on Image Processing, Neural Networks, and Data Mining are reviewed, discussed and compared. This survey emphasizes that Canny Edge Detection technique gives the better solution than other edge detective techniques in terms of vehicle identification. The Fuzzy c-means clustering and K nearest neighbor algorithms prove better for extracting the features of a vehicle like an area, length-width ratio etc.

Keywords: Vehicle classification, Neural Networks, Canny Edge Detection, Fuzzy c-means clustering, K nearest neighbor

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DOI: 01.1617/vol5/iss3/pid02457


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Editor-in-Chief

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Dr. Allon Guez
Professor, Drexel University,
USA


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IMPACT FACTOR: 4.890

ISSN(Online):2394-2320

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Thomson Reuters ID : q-6288-2016.
ORCiD Research ID : 0000-0001-9540-6799

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ACCEPTANCE RATIO

ACCEPTANCE RATIO: 28.69%
ARTICLES PUBLISHED:0521
PAPER RECEIVED:01730
Journal Code : IJERCSE
Electronic ISSN : 2394-2320
Impact Factor : 4.890
Frequency : monthly
Contact : info@ijercse.com


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