
This article proposes an effective method for real-time banknote recognition, using digital image processing. The new Series 7 New Zealand banknotes are considered, as a case study, for intelligent real-time recognition. The composite feature of a banknote containing the elements of color and texture is extracted, and a three-layer back-propagation neural network is trained for classification. The proposed method has demonstrated excellent recognition results in an indoor environment and is comparatively less time-consuming that makes it suitable for real-time applications. This article fills in the vacancy of real-time recognition of the newly released paper currency. Practically, our proposed approach can be served as the uppermost for the future development of the prototype assisting the blind or the visually impaired in recognizing the new series of New Zealand banknotes.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 6 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
