A paper currency number recognition based on fast Adaboost training algorithm
As Adaboost has a good performance in classification, it is widely used in pattern recognition. However it takes long time to generate the weak classifiers. For improving the training speed, this paper presents a fast Adaboost weak classifier training algorithm. Firstly, sort the Eigen values to an...
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| creator | Hai-dong Wang Leye Gu Linping Du |
| description | As Adaboost has a good performance in classification, it is widely used in pattern recognition. However it takes long time to generate the weak classifiers. For improving the training speed, this paper presents a fast Adaboost weak classifier training algorithm. Firstly, sort the Eigen values to an array from small to large, and then traverse the sorted array once to find the best threshold and bias. The experimental results show that this improved algorithm can increase the training speed by 6 to 8 times. |
| doi_str_mv | 10.1109/ICMT.2011.6002079 |
| format | Conference Proceeding |
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| language | chi ; eng |
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| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Arrays Binary trees Classification algorithms Computer applications Face detection fast training algorithm optimal threshold Pattern recognition Training weak classifier |
| title | A paper currency number recognition based on fast Adaboost training algorithm |
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