Title :
A Classification Method for the Dirty Factor of Banknotes Based on Neural Network with Sine Basis Functions
Author :
He, Kexue ; Peng, Shurong ; Li, Shutao
Author_Institution :
Coll. of Electr. & Inf. Eng., Changsha Univ. of Sci. & Technol., Changsha
Abstract :
The classification on the dirty factor of the new and used banknotes is an important function of the note sorter. This paper proposes a classification method based on neural network with sine basis functions. The gray level histogram of banknote image is used as the characteristic vector to train the neural network. The classification effect is satisfying by this method.
Keywords :
bank data processing; image classification; image segmentation; learning (artificial intelligence); neural nets; probability; statistical analysis; vectors; banknote dirty factor; banknote image classification method; characteristic vector; gray level histogram; image segmentation; neural network training; probability distribution; sine basis function; Automation; Computer networks; Educational institutions; Feature extraction; Histograms; Intelligent networks; Neural networks; Neurons; Probability distribution; Sorting; banknotes; classification; dirty factor; neural network;
Conference_Titel :
Intelligent Computation Technology and Automation (ICICTA), 2008 International Conference on
Conference_Location :
Hunan
Print_ISBN :
978-0-7695-3357-5
DOI :
10.1109/ICICTA.2008.35
