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학술지 Real-Time License Plate Detection in High-Resolution Videos Using Fastest Available Cascade Classifier and Core Patterns
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저자
한병길, 이종택, 임길택, 정윤수
발행일
201504
출처
ETRI Journal, v.37 no.2, pp.251-261
ISSN
1225-6463
출판사
한국전자통신연구원 (ETRI)
DOI
https://dx.doi.org/10.4218/etrij.15.2314.0077
초록
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 제안 키워드
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