Neuro Recognizer: Neural Network Based Hand-Written Character Recognition

Authors

  • K Radha Revathi Department of MCA, Swarnandhra College of Engineering & Technology, JNTUK University, Narsapuram
  • ANL Kumar Department of MCA, Swarnandhra College of Engineering & Technology, JNTUK University, Narsapuram
  • Krishnaji A Department of MCA, Swarnandhra College of Engineering & Technology, JNTUK University, Narsapuram

Keywords:

OCR, MCR, ANN, Character Recognition, Back Propagation Algorithm

Abstract

This paper presents an Artificial Neural Network (ANN) based approach for the recognition of handwritten characters in the presence of noise because now a days the handwritten recognition place a crucial role in various industrial applications. In the Handwritten recognition noise has been regarded as one of the major issue that degrades the performance of character recognition system. So to recognize the handwritten characters in different noise levels, In order to overcome this limitation, the back propagation (BP based ANN) is designed for the handwritten character recognition. The recognition system is designed and tested in JAVA under different noise levels. Experimental results indicate that the proposed approach can obtain very high recognition rate for all handwritten characters in the presence of noise.

References

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Published

2025-11-10

How to Cite

[1]
K. Radha Revathi, A. Kumar, and A. Krishnaji, “Neuro Recognizer: Neural Network Based Hand-Written Character Recognition”, Int. J. Comp. Sci. Eng., vol. 3, no. 9, pp. 28–33, Nov. 2025.

Issue

Section

Research Article