Recognition of Off-Line Handwritten Kannada Words Using Enhanced Skew Detection and Correction Method

Authors

  • Shakunthala B. S Associate Professor, Department of ISE, Kalpataru Institute of Technology, Tiptur, Karnataka, India
  • Ullas H. S Research Scholar, Department of E & C, Sri Siddhartha Institute of Technology, Tumkur, Karnataka, India
  • Pillai C. S Professor, Department of CSE. ACS College of Engineering, Bangalore, Karnataka, India

DOI:

https://doi.org/10.34293/acsjse.v3iS1.93

Keywords:

Skew detection and correction, Preprocessing, Segmentation

Abstract

Handwritten character image is taken as dataset for this method. In the proposed system, extracting text lines, word, charactersand skew correction are done based on Enhanced Skew Detection and Correction for Words algorithm for estimating and correcting skew lines. The algorithm will be used for finding the height andwidth of the entire handwritten word. In case of no skew, minimum valuewill be considered for the height of the wordand maximum value will be considered for the width of the word. Once skew is corrected with approximateskew angle repetition of the same process, only busy zone is considered for performing precise skewcorrection. The recommended approach has tested roughly 3364 Kannada items and achieved the best performance of 97.05 percent.

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Published

02-01-2024

Issue

Section

Articles