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
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