Two-dimensional signal and image processing
Two-dimensional signal and image processing
Multiple Kinds of Paper Currency Recognition Using Neural Network and Application for Euro Currency
IJCNN '00 Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN'00)-Volume 2 - Volume 2
Authentication of currency notes through printing technique verification
Proceedings of the Seventh Indian Conference on Computer Vision, Graphics and Image Processing
Recognition of Mexican banknotes via their color and texture features
Expert Systems with Applications: An International Journal
Hi-index | 12.05 |
Accurate characterization is an important issue in paper currency recognition system. This paper proposes a robust paper currency recognition method based on Hidden Markov Model (HMM). By employing HMM, the texture characteristics of paper currencies are modeled as a random process. The proposed algorithm can be used for distinguishing paper currency from different countries. A similarity measure has been used for the classification in the proposed algorithm. To evaluate the performance of the proposed algorithm, experiments have been conducted on more than 100 denominations from different countries. The results indicate 98% accuracy for recognition of paper currency.