Invariant Primitives for Handwritten Arabic Script: A Contrastive Study of Four Feature Sets

The choice of relevant features is very decisive in handwriting recognition rate. Our aim is to present some useful structural and statistical features and see their degree of variability. In this paper, we start with a description of the variability of the Arabic handwriting and the way how to redu...

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Bibliographic Details
Main Authors: Haboubi, S., Maddouri, S., Ellouze, N., El-Abed, H.
Format: Conference Proceeding
Language:English
Subjects:
Arabic script
Data mining
Handwriting recognition
IFN/ENIT
Image analysis
Image databases
Image recognition
Image segmentation
Invariant Primitives
Pattern recognition
Skeleton
Spatial databases
Text analysis
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Summary:The choice of relevant features is very decisive in handwriting recognition rate. Our aim is to present some useful structural and statistical features and see their degree of variability. In this paper, we start with a description of the variability of the Arabic handwriting and the way how to reduce it. Four kinds of feature sets used by our handwriting systems are then presented evaluated and discussed. The comparison is carried on a database of images from IFN/ENIT databases. The neural network multilayer perceptrons is our method of classification. A contrastive study of these primitives is done according to recognition their time and memory consuming and their variability degree.
ISSN:1520-5363
2379-2140
DOI:10.1109/ICDAR.2009.281