Convolutional Neural Network Based Serial Number Recognition Method for Indian Rupee Banknotes

The recognition of the banknote serial number, which constitutes important data used for various purposes is one of the important functions of banknote counters. However, traditional character recognition methods are limited in terms of speed and performance of serial number recognition. Therefore, in this paper, we propose a character extraction method based on the aspect ratio of banknotes and a character recognition method based on a convolutional neural network (CNN). For character extraction, de-skewing was performed first. Then, the serial number was estimated on the basis of the aspect ratio of the banknote. Further, we designed four types of CNN-based neural networks for character recognition and adopted the most appropriate neural network. Subsequently, we confirmed that the average recognition performance per character for each neural network was 99.85%.

[1]  Bidyut Baran Chaudhuri,et al.  A complete printed Bangla OCR system , 1998, Pattern Recognit..

[2]  Mengjie Zhang,et al.  A Digit Recognition System for Paper Currency Identification Based on Virtual Instruments , 2006, 2006 International Conference on Information and Automation.

[3]  P.K Sahoo,et al.  A survey of thresholding techniques , 1988, Comput. Vis. Graph. Image Process..

[4]  Andreas Vrabl,et al.  Fast real-time recognition and quality inspection of printed characters via point correlation , 2001, IS&T/SPIE Electronic Imaging.

[5]  Li Wenhong,et al.  Application of support vector machine (SVM) on serial number identification of RMB , 2010, 2010 8th World Congress on Intelligent Control and Automation.

[6]  Ting-ting Zhao,et al.  Study on RMB number recognition based on genetic algorithm artificial neural network , 2010, 2010 3rd International Congress on Image and Signal Processing.

[7]  Parminder Singh Reel,et al.  Image Processing based Heuristic Analysis for Enhanced Currency Recognition , 2011 .

[8]  Ching Y. Suen,et al.  Automatic recognition of serial numbers in bank notes , 2014, Pattern Recognit..