A Comprehensive Approach for Real-Time Character Recognition System for Image Video and Handwritten Documents
Dr.(Mrs.) Jayshree R. Pansare
, Aditi Sunil Gaikwad. , Vaishnavi Ashok Ankam. , Priyanka Pandurang Karne. , Shikha sushil Sharma.
Real-Time Character Recognition, SVM, Optical Character Recognition (OCR), Deep Learning algorithms.
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.
"A Comprehensive Approach for Real-Time Character Recognition System for Image Video and Handwritten Documents", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.3, Issue 11, page no.268 - 273, December-2018, Available :https://ijsdr.org/papers/IJSDR1812045.pdf
Volume 3
Issue 11,
December-2018
Pages : 268 - 273
Paper Reg. ID: IJSDR_180921
Published Paper Id: IJSDR1812045
Downloads: 000347260
Research Area: Engineering
Country: Pune, Maharashtra, India
ISSN: 2455-2631 | IMPACT FACTOR: 9.15 Calculated By Google Scholar | ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.15 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: IJSDR(IJ Publication) Janvi Wave
