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Offline text-independent writer identification using codebook and efficient code extraction methods

delete2013-05-01
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G
Golnaz Ghiasi
R
Reza Safabakhsh *
DOI:10.1016/j.imavis.2013.03.002delete
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摘要

摘要

En 中文
In this paper, an efficient method for text-independent writer identification using a codebook method is proposed. The method uses the occurrence histogram of the shapes in a codebook to create a feature vector for each specific manuscript. For cursive handwritings, a wide variety of different shapes exist in the connected components obtained from the handwriting. Small fragments of connected components are used to avoid complex patterns. Two efficient methods for extracting codes from contours are introduced. One method uses the actual pixel coordinates of contour fragments while the other one uses a linear piece-wise approximation using segment angles and lengths. To evaluate the methods, writer identification is conducted on two English and three Farsi handwriting databases. Both methods show promising performances with the performance of second method being better than the first one. (C) 2013 Elsevier B.V. All rights reserved.
Keyword:
Handwritten documents
Writer identification
Farsi handwriting
English handwriting
Codebook
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Image and Vision Computing 封面图
Image and Vision Computing
IF:
4.2
论文数:
4.1K
被引数:
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机构

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Amirkabir University of Technology
学者数:
1.1W
论文数: 1.1W
被引数: 1.0W
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