A paper currency number recognition based on fast Adaboost training algorithm
Haidong Wang, Leye Gu, Linping Du · 2011
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.