Visual Pop-Can Detection Method Based on AdaBoost

Xin Yi Lin; Yan Bing Xue; Bao Hong Guo

doi:10.4028/www.scientific.net/AMM.548-549.637

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 548-549Visual Pop-Can Detection Method Based on AdaBoost

Visual Pop-Can Detection Method Based on AdaBoost

Abstract:

^{This paper puts forward a visual method of detecting pop-cans based on AdaBoost Algorithm. This method, is basing on the idea of AdaBoost Algorithm, and we use Haar Feature and LBP Feature to extract pop-can characteristics respectively. Finally we compare the differences of the training processes and the experiment results between these two detectors. It shows that these pop-can detectors that are trained by this visual method have high detection rate and speed.}

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Periodical:

Applied Mechanics and Materials (Volumes 548-549)

Pages:

637-640

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.548-549.637

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Online since:

April 2014

Authors:

Xin Yi Lin*, Yan Bing Xue, Bao Hong Guo

Keywords:

Adaboost Algorithm, Detector, Haar Feature, LBP Feature, Pop-Can

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* - Corresponding Author

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