Extraction of Tamil Characters from a Handwritten Document using Connected Component Labeling
|D. Rajalakshmi1 , S.K. Jayanthi2|
1 Dept. of Computer Science, Vellalar College for Women (Bharathiar University), Coimbatore, India.
2 Dept. of Computer Science, Vellalar College for Women (Bharathiar University), Coimbatore, India.
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Section:Research Paper, Product Type: Journal Paper
Volume-5 , Issue-9 , Page no. 141-146, Sep-2017
Online published on Sep 30, 2017
Copyright © D. Rajalakshmi, S.K. Jayanthi . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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IEEE Style Citation: D. Rajalakshmi, S.K. Jayanthi, “Extraction of Tamil Characters from a Handwritten Document using Connected Component Labeling”, International Journal of Computer Sciences and Engineering, Vol.5, Issue.9, pp.141-146, 2017.
MLA Style Citation: D. Rajalakshmi, S.K. Jayanthi "Extraction of Tamil Characters from a Handwritten Document using Connected Component Labeling." International Journal of Computer Sciences and Engineering 5.9 (2017): 141-146.
APA Style Citation: D. Rajalakshmi, S.K. Jayanthi, (2017). Extraction of Tamil Characters from a Handwritten Document using Connected Component Labeling. International Journal of Computer Sciences and Engineering, 5(9), 141-146.
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|Writer identification is a challenging task for the reason that it requires textural features and structural features. Textural features like grey-level co-occurrence matrices, Gabor filters can be extracted from entire page or a block of text. The structural features like slant and skew, character height, stroke width, frequency of loops or blobs etc. also characterize the handwriting style. Before extracting character level features it is a prerequisite to segment the document image into characters. This paper proposes a connected component oriented approach to segment an image of handwritten Tamil document into individual characters. The features extracted from these characters then can be used for writer identification.|
|Key-Words / Index Term :|
|Writer Identification, Handwritten documents, Segmentation, Connected Component, Tamil Script|
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