Classification of Vehicles using SURF Technique & SVM Classifier
DOI:
https://doi.org/10.26438/ijcse/v5i9.194197Keywords:
SURF, vehicle classification, Feature extraction, SVM classifier, BOFAbstract
There has been an enormous increase in the number and types of vehicles on the roads with the increase in population. Vehicle Classification (VC) has become an important subject of study in the last few years because of its importance in security system, traffic congestion avoidance, traffic management etc. This paper implements vehicle classification on the basis of appearance based technique “Speeded up Robust Features” (SURF) descriptor and Support Vector Machine (SVM) classifier. Keeping this as focal point, SURF Technique is used for the purpose of feature extraction from the images in form of descriptor and then matches these feature points of training images and test images whereas SVM classifier is used to classify images based on the outcome of feature points. Through the experiment and analysis of results, the proposed methodology provides better results in terms of accuracy and matching time.
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