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Journal Article Real-Time License Plate Detection in High-Resolution Videos Using Fastest Available Cascade Classifier and Core Patterns
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Authors
Byung-Gil Han, Jong Taek Lee, Kil-Taek Lim, Yunsu Chung
Issue Date
2015-04
Citation
ETRI Journal, v.37, no.2, pp.251-261
ISSN
1225-6463
Publisher
한국전자통신연구원 (ETRI)
Language
English
Type
Journal Article
DOI
https://dx.doi.org/10.4218/etrij.15.2314.0077
Project Code
14ZI2200, 대경권 지역전략산업 기반 융합기술 지원사업, Chung Yun Su
Abstract
We present a novel method for real-time automatic license plate detection in high-resolution videos. Although there have been extensive studies of license plate detection since the 1970s, the suggested approaches resulting from such studies have difficulties in processing high-resolution imagery in real-time. Herein, we propose a novel cascade structure, the fastest classifier available, by rejecting false positives most efficiently. Furthermore, we train the classifier using the core patterns of various types of license plates, improving both the computation load and the accuracy of license plate detection. To show its superiority, our approach is compared with other state-of-the-art approaches. In addition, we collected 20,000 images including license plates from real traffic scenes for comprehensive experiments. The results show that our proposed approach significantly reduces the computational load in comparison to the other state-ofthe-art approaches, with comparable performance accuracy.
KSP Keywords
Cascade Classifier, Cascade structure, False positive, High-resolution, License Plate Detection, Performance accuracy, Real-Time, computation load, computational load, novel method, state-of-The-Art