Handwritten Digits and Optical Characters Recognition

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Published: May 4, 2023
DOI: https://doi.org/10.17762/ijritcc.v11i4.6376
Keywords:
Optical Character Recognition, CNN model, Handwritten character recognition, hidden layer

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Kartik Sharma
School of Electronics Engineering, Vellore Institute of Technology, Vellore, India
S.V. Jagadeesh Kona
School of Electronics Engineering, Vellore Institute of Technology, Vellore, India
Anshul Jangwal
School of Electronics Engineering, Vellore Institute of Technology, Vellore, India
Aarthy M
School of Electronics Engineering, Vellore Institute of Technology, Vellore, India
Prayline Rajabai C
School of Electronics Engineering, Vellore Institute of Technology, Vellore, India
Deepika Rani Sona
School of Electronics Engineering, Vellore Institute of Technology, Vellore, India

Abstract

The process of transcribing a language represented in its spatial form of graphical characters into its symbolic representation is called handwriting recognition. Each script has a collection of characters or letters, often known as symbols, that all share the same fundamental shapes. Handwriting analysis aims to correctly identify input characters or images before being analysed by various automated process systems. Recent research in image processing demonstrates the significance of image content retrieval. Optical character recognition (OCR) systems can extract text from photographs and transform that text to ASCII text. OCR is beneficial and essential in many applications, such as information retrieval systems and digital libraries.

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How to Cite
Sharma, K. ., Kona, S. J. ., Jangwal, A. ., M, A. ., Rajabai C, P. ., & Sona, D. R. . (2023). Handwritten Digits and Optical Characters Recognition. International Journal on Recent and Innovation Trends in Computing and Communication, 11(4), 20–24. https://doi.org/10.17762/ijritcc.v11i4.6376
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Vol. 11 No. 4 (2023): April (2023) Issue
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Articles

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