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| A Simple Segmentation Approach for Unconstrained Cursive Handwritten Words in Conjunction with the Neural Network.
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Full
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Source |
International Journal of Image Processing (IJIP) |
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Table of Contents |
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Volume: 2 Issue: 3 |
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Pages: 1-35 |
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Publication
Date: June 2008 |
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ISSN
(Online): 1985-2304 |
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Pages |
29 - 35 |
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Author(s) |
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Published
Date |
16-09-2008 |
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Publisher |
CSC
Journals, Kuala Lumpur,
Malaysia |
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ADDITIONAL
INFORMATION |
| Keywords Abstract References Cited by Related Articles Collaborative
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KEYWORDS: Image analysis, Segmentation, Neural Network, Preprocessing, Pattern matching |
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| This paper presents a new, simple and fast approach for character segmentation of unconstrained handwritten words. The developed segmentation algorithm over-segments in some cases due to the inherent nature of the cursive words. However the over segmentation is minimum. To increase the efficiency of the algorithm an Artificial Neural Network is trained with significant amount of valid segmentation points for cursive words manually. Trained neural network extracts incorrect segmented points efficiently with high speed. For fair comparison benchmark database IAM is used. The experimental results are encouraging.
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G. Sulong , A. Rehman and T. Saba."Improved Offline Connected Script Recognition Based on Hybrid Strategy".International Journal of Engineering Science and Technology, 2(6):1603-1611, 2010
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| 2 |
A. Rehman, D. Mohamad, G. Sulong."Implicit Vs Explicit based Script Segmentation and Recognition: A Performance Comparison on Benchmark Database". Int. J. Open Problems Compt. Math,2(3):352-364, 2009
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| Amjad Rehman Khan : Colleagues
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| Zulkifli Mohammad : Colleagues
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