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학술지 Robust Sign Recognition System at Subway Stations Using Verification Knowledge
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저자
이동진, 윤호섭, 정명애, 김재홍
발행일
201410
출처
ETRI Journal, v.36 no.5, pp.696-703
ISSN
1225-6463
출판사
한국전자통신연구원 (ETRI)
DOI
https://dx.doi.org/10.4218/etrij.14.2214.0007
협약과제
13SE1600, 시각 생체 모방 소자 및 인지 시스템 기술 개발, 정명애
초록
In this paper, we present a walking guidance system for the visually impaired for use at subway stations. This system, which is based on environmental knowledge, automatically detects and recognizes both exit numbers and arrow signs from natural outdoor scenes. The visually impaired can, therefore, utilize the system to find their own way (for example, using exit numbers and the directions provided) through a subway station. The proposed walking guidance system consists mainly of three stages: (a) sign detection using the MCT-based AdaBoost technique, (b) sign recognition using support vector machines and hidden Markov models, and (c) three verification techniques to discriminate between signs and non-signs. The experimental results indicate that our sign recognition system has a high performance with a detection rate of 98%, a recognition rate of 99.5%, and a false-positive error rate of 0.152.
키워드
Character recognition, Hidden Markov model, HMM, Natural-scene images, Sign detection, Sign recognition, Support vector machine, SVM, Verification
KSP 제안 키워드
Environmental knowledge, High performance, Recognition System, Recognition rate, Scene images, Sign detection, Support VectorMachine(SVM), Verification Techniques, Visually impaired, character recognition, detection rate(DR)