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Line Segmentation in Handwritten Assamese and Meetei Mayek Script Using Seam Carving Based Algorithm

  • Chandan Jyoti Kumar
  • Sanjib Kr. Kalita
Conference paper
Part of the Springer Proceedings in Physics book series (SPPHY, volume 166)

Abstract

Line segmentation is a key stage in an Optical Character Recognition system. This paper primarily concerns the problem of text line extraction on color and grayscale manuscript pages of two major North-east Indian regional Scripts, Assamese and Meetei Mayek. Line segmentation of handwritten text in Assamese and Meetei Mayek scripts is an uphill task primarily because of the structural features of both the scripts and varied writing styles. Line segmentation of a document image is been achieved by using the Seam carving technique, in this paper. Researchers from various regions used this approach for content aware resizing of an image. However currently many researchers are implementing Seam Carving for line segmentation phase of OCR. Although it is a language independent technique, mostly experiments are done over Arabic, Greek, German and Chinese scripts. Two types of seams are generated, medial seams approximate the orientation of each text line, and separating seams separated one line of text from another. Experiments are performed extensively over various types of documents and detailed analysis of the evaluations reflects that the algorithm performs well for even documents with multiple scripts. In this paper, we present a comparative study of accuracy of this method over different types of data.

Keywords

Document Image Text Line Line Segmentation Handwritten Text Handwritten Document 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer India 2015

Authors and Affiliations

  1. 1.Department of Computer ScienceGauhati UniversityGauhatiIndia

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