Multiresolution Gray-Scale and Rotation Invariant Texture Classification with Local Binary Patterns
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Hierarchical Classification Method for US Bank-Notes*This paper was presented at MVA2005.
IEICE - Transactions on Information and Systems
Using Hidden Markov Models for paper currency recognition
Expert Systems with Applications: An International Journal
Multi-banknote identification using a single neural network
ACIVS'05 Proceedings of the 7th international conference on Advanced Concepts for Intelligent Vision Systems
A neural network-based model for paper currency recognition and verification
IEEE Transactions on Neural Networks
High speed paper currency recognition by neural networks
IEEE Transactions on Neural Networks
Performance analysis of colour descriptors for parquet sorting
Expert Systems with Applications: An International Journal
Hi-index | 12.05 |
In this paper it is introduced a recognition method for Mexican banknotes by using artificial vision. It is shown that the Mexican banknotes can be classified by extracting their color and texture features, with the RGB space and the Local Binary Patterns, respectively. We show the classification results performed with the current Mexican banknotes. We state that the proposed method can be applied to recognize banknotes of other countries which employ colors to distinguish the denominations.