Name
Abstract | ||
|---|---|---|
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. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1016/j.eswa.2012.02.132 | Expert Syst. Appl. |
Keywords | Field | DocType |
mexican banknote,recognition method,current mexican banknote,artificial vision,local binary patterns,classification result,rgb space,texture feature | Computer vision,Computer science,Local binary patterns,Artificial intelligence,RGB color model,Invariant (mathematics),Texture recognition,Artificial vision | Journal |
Volume | Issue | ISSN |
39 | 10 | 0957-4174 |
Citations | PageRank | References |
12 | 0.81 | 11 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Farid GarcíA Lamont | 1 | 69 | 9.58 |
| Jair Cervantes | 2 | 176 | 18.08 |
| Asdrúbal López Chau | 3 | 87 | 11.62 |