DocumentCode :
3364693
Title :
Empirical analysis of AdaBoost algorithms on license plate detection
Author :
Sun, Junxi ; Cui, Dong ; Gu, Dongbing ; Hua Cai ; Liu, Guangwen
Author_Institution :
Sch. of Electron. & Inf. Eng., Changchun Univ. of Sci. & Technol., Changchun, China
fYear :
2009
fDate :
9-12 Aug. 2009
Firstpage :
3497
Lastpage :
3502
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.
Keywords :
image recognition; AdaBoost algorithms empirical analysis; license plate detection; license plate recognition technology; Algorithm design and analysis; Automation; Boosting; Information analysis; Iterative algorithms; Layout; Licenses; Object detection; Object recognition; Sun; AdaBoost algorithm; License plate detection; weak classifier;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Mechatronics and Automation, 2009. ICMA 2009. International Conference on
Conference_Location :
Changchun
Print_ISBN :
978-1-4244-2692-8
Electronic_ISBN :
978-1-4244-2693-5
Type :
conf
DOI :
10.1109/ICMA.2009.5246285
Filename :
5246285
Link To Document :
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