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An Improved Approach for Devanagari Handwritten Characters Recognition System

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Applied Information Processing Systems

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1354))

Abstract

It is a very complicated task to recognize the handwritten characters and scanned data/images in recent years. The different sizes and writing methods of the characters play a critical role in clearly identifying the handwritten characters. This script's massive prevalence must be taken care of by using advanced technologies to connect to the real world to a greater depth. Machine Learning is one of the most popular technologies that has attracted the recent research work of handwritten character recognition using A.I. techniques. Various new technologies have been developed to execute fast neural networks with little exhaustive knowledge requirements. Here, we operate using Keras and Python libraries for building our model. The main aim of CNN is to recognize the training data and fit that training data into models that should help human beings. In this paper, an attempt has been made to construct and evaluate a simple individual learning algorithm (like k-means and SVM) using Keras to recognize isolated Devanagari handwritten characters datasets and assess the impact of variations in parameters in the learning phase. The proposed methodology gives a better result. The accuracy is better than individual algorithm performance.

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Author information

Authors and Affiliations

  1. School of Computer Science & Applications, IFTM University, Moradabad, India

    Rajdeep Singh, Arvind Kumar Shukla & Rahul Kumar Mishra

  2. Department of CS&IT, MJP Rohilkhand University, Bareilly, UP, India

    S. S. Bedi

Authors
  1. Rajdeep Singh
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  2. Arvind Kumar Shukla
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  3. Rahul Kumar Mishra
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  4. S. S. Bedi
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Editor information

Editors and Affiliations

  1. Department of Electronics and Telecommunications Engineering, Dr. Babasaheb Ambedkar Technological University, Lonere, India

    Brijesh Iyer

  2. Department of Electronics and Computer Engineering, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand, India

    Debashis Ghosh

  3. Department of Automatics and Applied Software, Aurel Vlaicu University of Arad, Arad, Romania

    Valentina Emilia Balas

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Singh, R., Shukla, A.K., Mishra, R.K., Bedi, S.S. (2022). An Improved Approach for Devanagari Handwritten Characters Recognition System. In: Iyer, B., Ghosh, D., Balas, V.E. (eds) Applied Information Processing Systems . Advances in Intelligent Systems and Computing, vol 1354. Springer, Singapore. https://doi.org/10.1007/978-981-16-2008-9_20

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