Thesis Details
Detekce a rozpoznání registrační značky z fotografie
This thesis describes the design and implementation of system for detection and recognition of license plate. This system is divided into three parts which are license plate detection, character segmentation and optical character recognition. License plate detection is done by cascade classifier that achieves hit rate of 95.5% and precision rate of 95.9%. Character segmentation is based on contour finding that achieves hit rate of 93.3% and precision rate of 96.5%. Optical character recognition is done by neural network and achieves hit rate of 98.4% for individual characters. The whole system is able to detect and recognize up to 81.5% of license plates from the test data set.
license plate, license plate detection, cascade classifier, AdaBoost, optical character recognition, neural network, segmentation
Drahanský Martin, prof. Ing., Dipl.-Ing., Ph.D. (DITS FIT BUT), člen
Chudý Peter, doc. Ing., Ph.D. MBA (DCGM FIT BUT), člen
Očenášek Pavel, Mgr. Ing., Ph.D. (DIFS FIT BUT), člen
Strnadel Josef, Ing., Ph.D. (DCSY FIT BUT), člen
@bachelorsthesis{FITBT18706,
author = "Kry\v{s}tof Jan\'{i}\v{c}ek",
type = "Bachelor's thesis",
title = "Detekce a rozpozn\'{a}n\'{i} registra\v{c}n\'{i} zna\v{c}ky z fotografie",
school = "Brno University of Technology, Faculty of Information Technology",
year = 2016,
location = "Brno, CZ",
language = "czech",
url = "https://www.fit.vut.cz/study/thesis/18706/"
}