Learning banknote fitness for sorting

In this work, a machine learning method is proposed for banknote soiling determination. We apply proven techniques from computer vision to come up with a robust and effective method for automatic sorting of banknotes. The proposed method is evaluated with respect to various invariance classes. The method shows excellent performance on a large validation set of over 8,000 banknotes from the Eurosystem, while being learned on only 300 banknotes per denomination.

[1]  Paul A. Viola,et al.  Robust Real-Time Face Detection , 2001, Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001.

[2]  Cor J. Veenman,et al.  Visual Word Ambiguity , 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[3]  Yoav Freund,et al.  A decision-theoretic generalization of on-line learning and an application to boosting , 1997, EuroCOLT.

[4]  Yoav Freund,et al.  A decision-theoretic generalization of on-line learning and an application to boosting , 1995, EuroCOLT.