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Degraded offline handwritten Gurmukhi character recognition: study of various features and classifiers

  • Anupam GargEmail author
  • Manish Kumar Jindal
  • Amanpreet Singh
Original Research

Abstract

Recognition of degraded offline handwritten characters of Gurmukhi script is very challenging task due to the complex structural properties of the script, which is not matter-of-fact in majority of other scripts. A study based on the combination of various feature extraction techniques for character recognition has been presented in this paper. By extracting statistical features in hierarchical order from the pre-segmented degraded offline handwritten Gurmukhi characters, the potential results are analyzed for the recognition. Four types of feature extraction techniques, namely, zoning, diagonal, peak extent based features (horizontally and vertically) and shadow features have been considered in the present study. For classification, three classifiers, specifically, k-NN, decision tree and random forest are employed to demonstrate the effect on the problem of degraded offline handwritten Gurmukhi character recognition. Authors have collected 8960 samples which are partitioned using the partitioning strategy and fivefold cross validation technique. In partitioning strategy, 80% of data is taken as the training dataset and remaining 20% data is considered as the testing dataset. Various parameters for performance measures such as recognition accuracy, false rejection rate (FRR), area under curve (AUC) and root mean square error (RMSE) are also used for analyzing the performance of features and classifiers.

Keywords

Degraded character recognition Handwriting recognition Feature extraction Classification 

Notes

Acknowledgements

I would like to thank, Department of Computer Science and Engineering, IKG Punjab Technical University to support in the study of the topic and to get the results of better quality. I am also grateful to the members of evaluation committee for their numerous support in overcoming obstacles I have been facing through my research.

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Copyright information

© Bharati Vidyapeeth's Institute of Computer Applications and Management 2019

Authors and Affiliations

  • Anupam Garg
    • 1
    Email author
  • Manish Kumar Jindal
    • 2
  • Amanpreet Singh
    • 3
  1. 1.Research Scholar, Department of Computer Science and EngineeringI. K. G. Punjab Technical UniversityJalandharIndia
  2. 2.Department of Computer Science and ApplicationsPanjab University Regional CentreMuktsarIndia
  3. 3.Department of Electronics and Communication EngineeringI. K. G. Punjab Technical UniversityJalandharIndia

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