COMPREHENSIVE STUDY OF DEEP LEARNING BASED TELUGU OCR

AUTHOR(S)

Dr. M.V. Vijaya Saradhi, K. Rakesh, D. Ravi Prasanna, K. Swetha, B. Praveen

DOI: https://doi.org/10.46647/ijetms.2023.v07i03.133

ABSTRACT
The aim of the project is to understand offline One of the most popular and difficult pattern recognition subjects is the use of optical character recognition (OCR) to read handwritten Telugu letters. This study suggests a three-stage OCR solution for Telugu documents that includes pre-processing, feature extraction, and classification. For the extraction of boundary edge pixel points during preprocessing, we used median filtering on the input characters as well as normalisation and skeletonization techniques. Each character is initially divided into three 3x3 grids during the feature extraction stage, and the associated centroid for each of the nine zones is assessed. This allows us to recognise characters in various styles. Following that, we drew the projection angel's horizontal and vertical symmetry to the character's closest pixel.

Page No: 874 - 877

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How to Cite This Article:
Dr. M.V. Vijaya Saradhi, K. Rakesh, D. Ravi Prasanna, K. Swetha, B. Praveen .COMPREHENSIVE STUDY OF DEEP LEARNING BASED TELUGU OCR . ijetms;7(3):874-877. DOI: 10.46647/ijetms.2023.v07i03.133