The Transactions of The Korean Institute of Electrical Engineers (전기학회논문지)

The Korean Institute of Electrical Engineers (대한전기학회)
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Image Feature-based Electric Vehicle Detection and Classification System Using Machine Learning

머신 러닝을 이용한 영상 특징 기반 전기차 검출 및 분류 시스템

  • Kim, Sanghyuk (Dept. of Electronic Engineering, Sogang University) ;
  • Kang, Suk-Ju (Dept. of Electronic Engineering, Sogang University)
  • Received : 2017.05.30
  • Accepted : 2017.06.19
  • Published : 2017.07.01
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Abstract

This paper proposes a novel way of vehicle detection and classification based on image features. There are two main processes in the proposed system, which are database construction and vehicle classification processes. In the database construction, there is a tight censorship for choosing appropriate images of the training set under the rigorous standard. These images are trained using Haar features for vehicle detection and histogram of oriented gradients extraction for vehicle classification based on the support vector machine. Additionally, in the vehicle detection and classification processes, the region of interest is reset using a number plate to reduce complexity. In the experimental results, the proposed system had the accuracy of 0.9776 and the $F_1$ score of 0.9327 for vehicle classification.

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References

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