A Novel Lexicon Reduction Method for Arabic Handwriting Recognition

Authors:
Safwan Wshah;Venu Govindaraju;Yanfen Cheng;Huiping Li
Affiliations:
-;-;-;-
Venue:
ICPR '10 Proceedings of the 2010 20th International Conference on Pattern Recognition
Year:
2010

Citing 0
Cited 3

TSV-LR: topological signature vector-based lexicon reduction for fast recognition of pre-modern Arabic subwords

Proceedings of the 2011 Workshop on Historical Document Imaging and Processing
W-TSV: Weighted topological signature vector for lexicon reduction in handwritten Arabic documents

Pattern Recognition
Offline arabic handwritten text recognition: A Survey

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Abstract

In this paper, we present a method for lexicon size reduction which can be used as an important pre-processing for an off-line Arabic word recognition. The method involves extraction of the dot descriptors and PAWs (Piece of Arabic Word ). Then the number and position of dots and the number of the PAWs are used to eliminate unlikely candidates. The extraction of the dot descriptors is based on defined rules followed by a convolutional neural network for verification. The reduction algorithm makes use of the combination of two features with a dynamic matching scheme. On IFN/ENIT database of 26459 Arabic handwritten word images we achieved a reduction rate of 87% with accuracy above 93%.