Blind Australians find great difficulty in recognising bank notes. Each note has the same feel, with no Braille markings, irregular edges or other tangible features. In Australia, there is only one device available that can assist blind people recognise their notes. Internationally, there are devices available; however they are expensive, complex and have not been developed to cater for Australian currency. This paper discusses a new device, the MoneyTalker that takes advantage of the largely different colours and patterns on each Australian bank note and recognises the notes electronically, using the reflection and transmission properties of light. Different coloured lights are transmitted through the inserted note and the corresponding sensors detect distinct ranges of values depending on the colour of the note. Various classification algorithms were studied and the final algorithm was chosen based on accuracy and speed of recognition. The MoneyTalker has shown an accuracy of more than 99%. A blind subject has tested the device and believes that it is usable, compact and affordable. Based on the devices that are available currently in Australia, the MoneyTalker is an effective alternative in terms of accuracy and usability.
[1]
D. Kibler,et al.
Instance-based learning algorithms
,
2004,
Machine Learning.
[2]
Ian H. Witten,et al.
Data mining: practical machine learning tools and techniques, 3rd Edition
,
1999
.
[3]
Raymond J. Mooney,et al.
Constructing Diverse Classifier Ensembles using Artificial Training Examples
,
2003,
IJCAI.
[4]
Ian H. Witten,et al.
Data mining: practical machine learning tools and techniques with Java implementations
,
2002,
SGMD.
[5]
Eibe Frank,et al.
Logistic Model Trees
,
2003,
Machine Learning.
[6]
Peter Norvig,et al.
Artificial Intelligence: A Modern Approach
,
1995
.
[7]
R. Klein,et al.
Causes and prevalence of visual impairment among adults in the United States.
,
2004,
Archives of ophthalmology.
[8]
John G. Cleary,et al.
K*: An Instance-based Learner Using and Entropic Distance Measure
,
1995,
ICML.