dc.contributor.author |
Assayony, Mohammed O. |
|
dc.contributor.author |
Mahmoud, Sabri A. |
|
dc.date.accessioned |
2018-07-05T10:17:25Z |
|
dc.date.available |
2018-07-05T10:17:25Z |
|
dc.date.issued |
2018-01-01 |
|
dc.identifier.issn |
2210-142X |
|
dc.identifier.uri |
http://10.7.0.19:8080/xmlui/handle/123456789/217 |
|
dc.description.abstract |
Holistic recognition of isolated words is an essential task in several daily life applications, e.g., bank check processing and postal address reading. In this work we present a system for the automatic recognition of Arabic handwritten words based on statistical features extracted by Bag-of-Features framework that exploits the discriminative power of Gabor features. A handwritten text image is filtered by a set of Gabor filters of different scales and orientations for extracting texture-based local features. The response of the Gabor filters are organized into two layouts, viz. the Statistical Gabor Features and Gabor Descriptors, and fed to the Bag-of-Features in order to produce statistical representations for the handwritten text. The produced features are utilized in a holistic handwritten word recognition system that is applied on handwritten Arabic checks legal amounts public dataset. The effective parameters of the two layouts as well as the Bag-of-Features framework are experimentally evaluated and the optimal values are used in reporting the final recognition accuracies. The best average recognition accuracy achieved by the produced features is 86.44% which is promising in such challenge dataset of large number of classes. |
en_US |
dc.language.iso |
en |
en_US |
dc.publisher |
University of Bahrain |
en_US |
dc.rights |
Attribution-NonCommercial-ShareAlike 4.0 International |
* |
dc.rights.uri |
http://creativecommons.org/licenses/by-nc-sa/4.0/ |
* |
dc.subject |
Holsitic handwriting recognition |
en_US |
dc.subject |
Arabic Handwriting Recognition |
en_US |
dc.subject |
Gabor Filters Response features |
en_US |
dc.subject |
Bag-of-Features |
en_US |
dc.title |
Recognition of Arabic Handwritten Words using Gabor-based Bag-of-Features Framework |
en_US |
dc.type |
Article |
en_US |
dc.identifier.doi |
http://dx.doi.org/10.12785/IJCDS/070104 |
|
dc.volume |
07 |
|
dc.issue |
01 |
|
dc.pagestart |
35 |
|
dc.pageend |
42 |
|
dc.source.title |
International Journal of Computing and Digital Systems |
|
dc.abbreviatedsourcetitle |
IJCDS |
|