DocumentCode :
2148191
Title :
Adaptive Zoning Features for Character and Word Recognition
Author :
Gatos, B. ; Kesidis, A.L. ; Papandreou, A.
Author_Institution :
Comput. Intell. Lab., Nat. Center for Sci. Res. Demokritos, Athens, Greece
fYear :
2011
fDate :
18-21 Sept. 2011
Firstpage :
1160
Lastpage :
1164
Abstract :
Zoning features are of the most popular and efficient statistical features that provide high speed and low complexity for character and word recognition. They are calculated by the density of pixels or pattern characteristics in several zones we divide the pattern frame. In this paper, we introduce the idea of adaptive zoning features that are extracted after adjusting the position of every zone based on local pattern information. This adjustment is performed by moving every zone towards the pattern body. This process is based on the maximization of the local pixel density around each zone. We have extensively tested our approach for character and word recognition as well as for using the pixel density or pattern characteristics in every zone. For all cases, we have recorded a significant improvement when the zoning features are used in the proposed adaptive way.
Keywords :
character recognition; feature extraction; image classification; optimisation; statistical analysis; word processing; adaptive zoning features; character recognition; feature extraction; local pixel density; maximization; pattern characteristics; pattern frame; statistical features; word recognition; Accuracy; Character recognition; Data mining; Feature extraction; Handwriting recognition; Skeleton; Character Recognition; Word Recognition; Zoning Features;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Document Analysis and Recognition (ICDAR), 2011 International Conference on
Conference_Location :
Beijing
ISSN :
1520-5363
Print_ISBN :
978-1-4577-1350-7
Electronic_ISBN :
1520-5363
Type :
conf
DOI :
10.1109/ICDAR.2011.234
Filename :
6065492
Link To Document :
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