Character Segmentation for Telugu Image Document using Multiple Histogram Projections

Authors

  • Prof E.Sreenivasa Reddy

  • anupama namburi

Keywords:

optical character recognition, segmentation, histogram projection, telugu scripts

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%).

How to Cite

Prof E.Sreenivasa Reddy, & anupama namburi. (2013). Character Segmentation for Telugu Image Document using Multiple Histogram Projections. Global Journal of Computer Science and Technology, 13(F5), 11–15. Retrieved from https://computerresearch.org/index.php/computer/article/view/174

Character Segmentation for Telugu Image Document using Multiple Histogram Projections

Published

2013-03-15