Open AccessEfficient method for vehicle license plate identification based on learning a morphological feature
Author(s) -
Wafy Maged,
Madbouly Ahmed M.M.
Publication year - 2016
Publication title -
iet intelligent transport systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.579
H-Index - 45
eISSN - 1751-9578
pISSN - 1751-956X
DOI - 10.1049/iet-its.2015.0064
Subject(s) - license , identification (biology) , artificial intelligence , feature (linguistics) , computer science , feature extraction , computer vision , pattern recognition (psychology) , automotive engineering , machine learning , engineering , linguistics , philosophy , botany , biology , operating system
The detection and identification of license plates from captured images have been widely studied over the past two decades. The demand for this technology in security and commercial applications ranges from traffic control organisation to parking management and vehicle tracking. License plate recognition can be divided into two steps: detection and identification. Recent algorithms have focused on the detection step, with few researchers studying identification. In this study, an algorithm is developed to detect and identify license plates. The algorithm is based on the fact that license plates have a semi‐symmetric distribution of corner points; it utilises morphological feature learning. The algorithm runs in real time, is highly robust, and can identify whether the candidate region contains a license plate.