By Topic

Empirical analysis of AdaBoost algorithms on license plate detection

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

5 Author(s)
Junxi Sun ; Sch. of Electron. & Inf. Eng., Changchun Univ. of Sci. & Technol., Changchun, China ; Dong Cui ; Dongbing Gu ; Hua Cai
more authors

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.

Published in:

Mechatronics and Automation, 2009. ICMA 2009. International Conference on

Date of Conference:

9-12 Aug. 2009