Research Repository

Empirical analysis of AdaBoost algorithms on license plate detection

Junxi Sun, and Dong Cui, and Dongbing Gu, and Hua Cai, and Guangwen Liu, (2009) Empirical analysis of AdaBoost algorithms on license plate detection. In: 2009 International Conference on Mechatronics and Automation (ICMA), 2009-08-09 - 2009-08-12.

Full text not available from this repository.

Abstract

AdaBoost algorithm is an effective license plate detection method in the field of license plate recognition technology. A through analysis of three boosting algorithms (namely Discrete, Real and Gentle AdaBoost) is presented for license plate detection, including the algorithm details and experiment comparisons. The experimental results show the Gentle AdaBoost algorithm obtains an overall better results in terms of high detection rate and low false positive rate than the discrete AdaBoost algorithm or real AdaBoost algorithm. ©2009 IEEE.

Item Type: Conference or Workshop Item (UNSPECIFIED)
Additional Information: Published proceedings: 2009 IEEE International Conference on Mechatronics and Automation, ICMA 2009
Uncontrolled Keywords: License plate detection; AdaBoost algorithm; weak classifier
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Science and Health
Faculty of Science and Health > Computer Science and Electronic Engineering, School of
SWORD Depositor: Elements
Depositing User: Elements
Date Deposited: 17 Sep 2013 10:50
Last Modified: 15 Jan 2022 00:44
URI: http://repository.essex.ac.uk/id/eprint/4658

Actions (login required)

View Item View Item