INTERNATIONAL JOURNAL OF SCIENTIFIC DEVELOPMENT AND RESEARCH International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016
open access , Peer-reviewed, and Refereed Journals, Impact factor 8.15
Text categorization is a challenging task when it comes to categorizing text from different sources such as images, videos, and handwritten text. Handwritten text may vary as per the diversified user. Hence, it is difficult to find the best technique to categorize such kind of texts due to the unavailability of standard dataset and evaluation measures. Our system presents a standard method for recognition of text from all kinds of aforementioned input sources using the Support Vector Machine (SVM) classifier. Additionally, it classifies and places the words into predefined classes of parts of speech for English language using Deep Learning algorithms.
Keywords:
Real-Time Character Recognition, SVM, Optical Character Recognition (OCR), Deep Learning algorithms.
Cite Article:
"A Comprehensive Approach for Real-Time Character Recognition System for Image Video and Handwritten Documents", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.3, Issue 11, page no.268 - 273, December-2018, Available :http://www.ijsdr.org/papers/IJSDR1812045.pdf
Downloads:
000337070
Publication Details:
Published Paper ID: IJSDR1812045
Registration ID:180921
Published In: Volume 3 Issue 11, December-2018
DOI (Digital Object Identifier):
Page No: 268 - 273
Publisher: IJSDR | www.ijsdr.org
ISSN Number: 2455-2631
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