Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/106987
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Title: Accurate car plate detection via car face landmark localization
Authors: Li, H 
Chiu, MY
Wu, K
Lei, Z
Lam, KM 
Issue Date: 2017
Source: Proceedings of SPIE : the International Society for Optical Engineering, 2017, v. 10420, 1042012
Abstract: For intelligent vehicle surveillance systems, it is a big challenge to detect small, blurred car plates of vehicles driving on a highway. In this paper, we present a novel, two-stage detection scheme for small, blurred car-plate detection in large surveillance images. Our proposed scheme firstly detects vehicles, and then locates the car plates in specific regions of detected vehicles based on our proposed car-face landmark localization algorithm. Our scheme can also solve the high false-alarming rate problem with small, blurred car-plate detection. Experimental results show that our proposed method is accurate, and able to reduce the false-alarming rate, without any compromise in speed.
Keywords: Car-plate detection
Intelligent traffic
Surveillance system
Vehicle detection and tracking
Publisher: SPIE - International Society for Optical Engineering
Journal: Proceedings of SPIE : the International Society for Optical Engineering 
ISBN: 978-1-5106-1304-1
978-1-5106-1305-8 (electronic)
ISSN: 0277-786X
EISSN: 1996-756X
DOI: 10.1117/12.2281924
Description: Ninth International Conference on Digital Image Processing (ICDIP 2017), 19-22 May 2017, Hong Kong, China
Rights: © (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this publication for a fee or for commercial purposes, and modification of the contents of the publication are prohibited.
The following publication Hailiang Li, Man-Yau Chiu, Kangheng Wu, Zhibin Lei, and Kin-Man Lam "Accurate car plate detection via car face landmark localization", Proc. SPIE 10420, Ninth International Conference on Digital Image Processing (ICDIP 2017), 1042012 (21 July 2017) is available at https://doi.org/10.1117/12.2281924.
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