Title
Noisy digit classification with multiple specialist
Abstract
A multi-classifier formed by specialised classifiers for noise produced by an image is shown in this work. A study has been carried out in the case of structure noisy images. Classifiers based on neighbourhood criteria are used in this work, the zoning global feature and the Euclidean distance too. The experiments have been carried out with images of typewritten digits, taken from forms of the Bank of Spain. Trying to obtain a strong database to support the experiments, we have added noise to the images of the digits. The recognition rate improves from 64.58% to 96.18%.
Year
DOI
Venue
2005
10.1007/11551188_66
ICAPR (1)
Keywords
Field
DocType
neighbourhood criterion,specialised classifier,euclidean distance,structure noisy image,strong database,recognition rate,multiple specialist,noisy digit classification,zoning global feature,typewritten digit
Computer science,Euclidean distance,Numerical digit,Speech recognition,Neighbourhood (mathematics)
Conference
Volume
ISSN
ISBN
3686
0302-9743
3-540-28757-4
Citations 
PageRank 
References 
1
0.36
14
Authors
3
Name
Order
Citations
PageRank
Andoni Cortés1444.52
F. Boto2414.75
clemente rodriguez3466.75