Philippine license plate detection and classification using faster R-CNN and feature pyramid network
Added Title
IEEE International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (11th : 2019)
HNICEM 2019
College
Gokongwei College of Engineering
Department/Unit
Manufacturing Engineering and Management
Document Type
Conference Proceeding
Source Title
2019 IEEE 11th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management, HNICEM 2019
Publication Date
11-1-2019
Abstract
The advancement of image and video processing using Artificial Intelligence (AI) have brought more significance to the role of Automatic License Plate Recognition (ALPR) systems in law enforcement and intelligent transport systems (ITS). However, the adaptation of such a system in the Philippines has been a challenge due to the different variations of Philippine license plates. In this paper, a neural network-based model for the detection and classification of different Philippine license plate formats is proposed. The proposed method classifies license plates into four categories - 1981, 2003, 2014, and other series.
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Digitial Object Identifier (DOI)
10.1109/HNICEM48295.2019.9072754
Recommended Citation
Brillantes, A., Billones, C. D., Amon, M., Cero, C., Jose, J. C., Billones, R. C., & Dadios, E. P. (2019). Philippine license plate detection and classification using faster R-CNN and feature pyramid network. 2019 IEEE 11th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management, HNICEM 2019 https://doi.org/10.1109/HNICEM48295.2019.9072754
Disciplines
Computer Engineering | Manufacturing
Keywords
Intelligent transportation systems; Automobile license plates
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