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Multi-layer Classification Approach for Online Handwritten Gujarati Character Recognition

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Computational Intelligence: Theories, Applications and Future Directions - Volume II

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 799))

Abstract

In this paper, the authors present a multi-layer classification approach for online handwritten character recognition for the Gujarati characters. The Gujarati language consists of many confusing characters which lead to misclassification. Multi-layer classification technique is proposed to increase the accuracy of confusing characters. In the first layer of classification, SVM classifier with the polynomial kernel is used with all training data. If first layer classifier returns a character which can be confused with some characters than in the second layer, SVM with the linear kernel is used with confusing characters’ training data. A hybrid feature set consisting zoning features and dominant point-based normalized chain code feature is used in both layers of classification. The system is trained using a data set of 2000 samples and tested by 200 different writers. The authors have achieved an average accuracy of 94.13% with an average processing time of 0.103 s per stroke.

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Acknowledgements

The authors acknowledge the support of University Grants Commission (UGC), New Delhi, for this research work through project file no. F. 42-127/2013.

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Authors and Affiliations

  1. Department of Computer Science, Veer Narmad South Gujarat University, Surat, Gujarat, India

    Vishal A. Naik & Apurva A. Desai

Authors
  1. Vishal A. Naik
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  2. Apurva A. Desai
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Corresponding author

Correspondence to Vishal A. Naik .

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Editors and Affiliations

  1. Department of Electrical Engineering, Indian Institute of Technology Kanpur, Kanpur, Uttar Pradesh, India

    Nishchal K. Verma

  2. Department of Aerospace Engineering, Indian Institute of Technology Kanpur, Kanpur, Uttar Pradesh, India

    A. K. Ghosh

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Naik, V.A., Desai, A.A. (2019). Multi-layer Classification Approach for Online Handwritten Gujarati Character Recognition. In: Verma, N., Ghosh, A. (eds) Computational Intelligence: Theories, Applications and Future Directions - Volume II. Advances in Intelligent Systems and Computing, vol 799. Springer, Singapore. https://doi.org/10.1007/978-981-13-1135-2_45

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