Open AccessMultiple licence plate detection for Chinese vehicles in dense traffic scenarios
Author(s) -
Asif Muhammad Rizwan,
Chun Qi,
Hussain Sajid,
Fareed Muhammad Sadiq
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.2016.0008
Subject(s) - chromatic scale , artificial intelligence , computer science , pixel , connected component labeling , computer vision , otsu's method , image processing , pattern recognition (psychology) , traffic congestion , color space , image (mathematics) , image segmentation , mathematics , engineering , transport engineering , combinatorics , scale space segmentation
In this study, the authors propose a real‐time multiple licence plate (LP) detection algorithm for dense traffic conditions which is of vital importance in this modern era due to increased traffic congestion. The chromatic component of YDbDr colour space is proposed to detect the blue regions, whereas a simple yet effective colour detection method is used to identify yellow LP regions. The low‐intensity pixel values are eliminated as a pre‐processing step to enhance the LP regions and Otsu method is used to obtain the binary image. The candidate regions are acquired by using the connected component analysis. The false candidate regions are by large rejected by inspecting the area and aspect ratio of LPs. Additionally, a two‐layered false LP detection approach has been introduced to remove fake LP regions. Experimental results in practical scenarios carried out in various weather conditions show that the proposed method is highly effective in coping with various illumination conditions to accurately detect the multiple vehicle LPs with an accuracy of 93.86%. The average processing time per image is 0.33 s that can achieve real‐time performance.