ETRI-Knowledge Sharing Plaform

ENGLISH

성과물

논문 검색
구분 SCI
연도 ~ 키워드

상세정보

학술지 Real-Time License Plate Detection in High-Resolution Videos Using Fastest Available Cascade Classifier and Core Patterns
Cited 30 time in scopus Download 8 time Share share facebook twitter linkedin kakaostory
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
협약과제
14ZI2200, 대경권 지역전략산업 기반 융합기술 지원사업, 정윤수
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.
키워드
Adaboost, Cascade classifier, License plate, LPR, Object detection
KSP 제안 키워드
Cascade Classifier, Cascade structure, False positive, High-resolution, License Plate Detection, Object detection, Performance accuracy, Real-Time, computation load, computational load, novel method