| Title |
Image Feature-based Electric Vehicle Detection and Classification System Using Machine Learning |
| Authors |
김상혁(Kim, Sanghyuk) ; 강석주(Kang, Suk-Ju) |
| DOI |
https://doi.org/10.5370/KIEE.2017.66.7.1092 |
| Keywords |
Machine Learning ; Supervised Learning ; Vehicle Classification |
| 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. |