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A fast and robust license plate detection algorithm based on two-stage cascade AdaBoost.

Sarker, Md. Mostafa Kamal; Yoon, Sook; Park, Dong Sun

Authors

Md. Mostafa Kamal Sarker

Sook Yoon

Dong Sun Park



Abstract

License plate detection (LPD) is one of the most important aspects of an automatic license plate recognition system. Although there have been some successful license plate recognition (LPR) methods in past decades, it is still a challenging problem because of the diversity of plate formats and outdoor illumination conditions in image acquisition. Because the accurate detection of license plates under different conditions directly affects overall recognition system accuracy, different methods have been developed for LPD systems. In this paper, we propose a license plate detection method that is rapid and robust against variation, especially variations in illumination conditions. Taking the aspects of accuracy and speed into consideration, the proposed system consists of two stages. For each stage, Haar-like features are used to compute and select features from license plate images and a cascade classifier based on the concatenation of classifiers where each classifier is trained by an AdaBoost algorithm is used to classify parts of an image within a search window as either license plate or non-license plate. And it is followed by connected component analysis (CCA) for eliminating false positives. The two stages use different image preprocessing blocks: image preprocessing without adaptive thresholding for the first stage and image preprocessing with adaptive thresholding for the second stage. The method is faster and more accurate than most existing methods used in LPD. Experimental results demonstrate that the LPD rate is 98.38% and the average computational time is 54.64 ms.

Citation

SARKER, M.M.K., YOON, S. and PARK, D.S. 2014. A fast and robust license plate detection algorithm based on two-stage cascade AdaBoost. KSII transactions on internet and information systems [online], 8(10), pages 3490-3507. Available from: https://doi.org/10.3837/tiis.2014.10.012

Journal Article Type Article
Acceptance Date Aug 22, 2014
Online Publication Date Oct 31, 2014
Publication Date Oct 31, 2014
Deposit Date Dec 4, 2021
Publicly Available Date Mar 29, 2024
Journal KSII Transactions on Internet and Information Systems
Electronic ISSN 2288-1468
Publisher KSII Korean Society for Internet Information
Peer Reviewed Peer Reviewed
Volume 8
Issue 10
Pages 3490-3507
DOI https://doi.org/10.3837/tiis.2014.10.012
Keywords License plate detection; Cascade classifier; Haar-like features; AdaBoost; Adaptive thresholding
Public URL https://rgu-repository.worktribe.com/output/1542193

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