Vehicle classification using AKAZE and feature matching approach and artificial neural network
College
Gokongwei College of Engineering
Department/Unit
Electronics And Communications Engg
Document Type
Conference Proceeding
Source Title
IEEE Region 10 Annual International Conference, Proceedings/TENCON
Volume
2018-October
First Page
1824
Last Page
1827
Publication Date
2-22-2019
Abstract
This research proposes a method in order to classify vehicles in a highly congested roads , a robust technique for vehicle classification with low computational power must be used. So, a proposed solution is to embed an AKAZE feature matching extraction which is ran in an artificial neural network will be used. AKAZE was used because it is faster than SIFT. The features extracted from the AKAZE algorithm will be grouped according to the type of vehicle where it was used and be placed to an Artificial Neural Network (ANN) for the training of the network itself. The results yielded good for real-time Vehicle Classification. © 2018 IEEE.
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Digitial Object Identifier (DOI)
10.1109/TENCON.2018.8650119
Recommended Citation
Bedruz, R. R., Fernando, A., Bandala, A. A., Sybingco, E., & Dadios, E. P. (2019). Vehicle classification using AKAZE and feature matching approach and artificial neural network. IEEE Region 10 Annual International Conference, Proceedings/TENCON, 2018-October, 1824-1827. https://doi.org/10.1109/TENCON.2018.8650119
Disciplines
Electrical and Computer Engineering | Electrical and Electronics | Systems and Communications
Keywords
Computer vision; Image registration; Image processing—Digital techniques; Neural networks (Computer science)
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