Name
Title | ||
|---|---|---|
Classification of Mexican Paper Currency Denomination by Extracting Their Discriminative Colors |
Abstract | ||
|---|---|---|
In this paper we describe a machine vision approach to recognize the denomination classes of the Mexican paper currency by extracting their color features. A banknote's color is characterized by summing all the color vectors of the image's pixels to obtain a resultant vector, the banknote's denomination is classified by knowing the orientation of the resulting vector within the RGB space. In order to obtain a more precise characterization of paper currency, the less discriminative colors of each denomination are eliminated from the images; the color selection is applied in the RGB and HSV spaces, separately. Experimental results with the current Mexican banknotes are presented. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1007/978-3-642-45111-9_35 | MICAI (2) |
Keywords | Field | DocType |
image processing | HSL and HSV,Pattern recognition,Machine vision,Computer science,Resultant,Image processing,Pixel,Banknote,Artificial intelligence,RGB color model,Discriminative model,Machine learning | Conference |
Citations | PageRank | References |
2 | 0.38 | 8 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Farid GarcíA Lamont | 1 | 69 | 9.58 |
| Jair Cervantes | 2 | 176 | 18.08 |
| Asdrúbal López Chau | 3 | 87 | 11.62 |
| Lisbeth Rodriguez | 4 | 24 | 2.75 |