Character Segmentation for Telugu Image Document using Multiple Histogram Projections

Article ID

CSTGV9KWE1

Character Segmentation for Telugu Image Document using Multiple Histogram Projections

N.Anupama
N.Anupama
Ch.Rupa
Ch.Rupa Department of Computer Science and Systems Engineering Andhra University
Prof E.Sreenivasa Reddy
Prof E.Sreenivasa Reddy Acharya Nagarjuna University,Guntur, AP, India.
DOI

Abstract

TEXT line segmentation is one of the major component of document image analysis. Text line segmentation is necessary to detect all text regions in the document image. In this paper we propose an algorithm based on multiple histogram projections using morphological operators to extract features of the image. Horizontal projection is performed on the text image, and then line segments are identified by the peaks in the horizontal projection. Threshold is applied to divide the text image into segments. False lines are eliminated using another threshold. Vertical histogram projections are used for the line segments and decomposed into words using threshold and further decomposed to characters. This approach provides best performance based on the experimental results such as Detection rate DR (98%) and Recognition Accuracy RA (98%).

Character Segmentation for Telugu Image Document using Multiple Histogram Projections

TEXT line segmentation is one of the major component of document image analysis. Text line segmentation is necessary to detect all text regions in the document image. In this paper we propose an algorithm based on multiple histogram projections using morphological operators to extract features of the image. Horizontal projection is performed on the text image, and then line segments are identified by the peaks in the horizontal projection. Threshold is applied to divide the text image into segments. False lines are eliminated using another threshold. Vertical histogram projections are used for the line segments and decomposed into words using threshold and further decomposed to characters. This approach provides best performance based on the experimental results such as Detection rate DR (98%) and Recognition Accuracy RA (98%).

N.Anupama
N.Anupama
Ch.Rupa
Ch.Rupa Department of Computer Science and Systems Engineering Andhra University
Prof E.Sreenivasa Reddy
Prof E.Sreenivasa Reddy Acharya Nagarjuna University,Guntur, AP, India.

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Prof E.Sreenivasa Reddy. 2013. “. Global Journal of Computer Science and Technology – F: Graphics & Vision GJCST-F Volume 13 (GJCST Volume 13 Issue F5): .

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Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

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GJCST Volume 13 Issue F5
Pg. 11- 15
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Character Segmentation for Telugu Image Document using Multiple Histogram Projections

N.Anupama
N.Anupama
Ch.Rupa
Ch.Rupa Department of Computer Science and Systems Engineering Andhra University
Prof E.Sreenivasa Reddy
Prof E.Sreenivasa Reddy Acharya Nagarjuna University,Guntur, AP, India.

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