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Feature selection to recognize text from palm leaf manuscripts

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Abstract

The medium for recording data and information in the present world is paper, magnetic tapes, hard disks, pen drives, etc., whereas about 700 years ago palm leaves were used for this purpose. To recognize the palm leaf text, a novel concept of using a 3D inherent feature, i.e., (depth of incision) is proposed in the current study. This proposed depth sensing approach is used for background subtraction on palm leaf manuscripts. For various features extracted from the palm leaf characters, an improved recognition accuracy is also reported with the help of this 3D feature. To improve the predictive recognition accuracy and to reduce the memory needed, investigations are carried out by implementing optimization techniques.

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Authors and Affiliations

  1. ECE Department, Mahatma Gandhi Institute of Technology, Gandipet, Telangana, India

    T. R. Vijaya Lakshmi

  2. ECE Department, Chaitanya Bharathi Institute of Technology, Gandipet, Telangana, India

    P. Narahari Sastry

  3. CSE Department, Srinidhi Institute of Science and Technology, Ghatkesar, Telangana, India

    T. V. Rajinikanth

Authors
  1. T. R. Vijaya Lakshmi
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  2. P. Narahari Sastry
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  3. T. V. Rajinikanth
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Correspondence to T. R. Vijaya Lakshmi.

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Vijaya Lakshmi, T.R., Sastry, P.N. & Rajinikanth, T.V. Feature selection to recognize text from palm leaf manuscripts. SIViP 12, 223–229 (2018). https://doi.org/10.1007/s11760-017-1149-9

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  • DOI: https://doi.org/10.1007/s11760-017-1149-9

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