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Real - Time Text Reader

by Jayshree R. Pansare, Aditi Gaikwad, Vaishnavi Ankam, Priyanka Karne, Shikha Sharma
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 182 - Number 34
Year of Publication: 2018
Authors: Jayshree R. Pansare, Aditi Gaikwad, Vaishnavi Ankam, Priyanka Karne, Shikha Sharma
10.5120/ijca2018918089

Jayshree R. Pansare, Aditi Gaikwad, Vaishnavi Ankam, Priyanka Karne, Shikha Sharma . Real - Time Text Reader. International Journal of Computer Applications. 182, 34 ( Dec 2018), 42-45. DOI=10.5120/ijca2018918089

@article{ 10.5120/ijca2018918089,
author = { Jayshree R. Pansare, Aditi Gaikwad, Vaishnavi Ankam, Priyanka Karne, Shikha Sharma },
title = { Real - Time Text Reader },
journal = { International Journal of Computer Applications },
issue_date = { Dec 2018 },
volume = { 182 },
number = { 34 },
month = { Dec },
year = { 2018 },
issn = { 0975-8887 },
pages = { 42-45 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume182/number34/30254-2018918089/ },
doi = { 10.5120/ijca2018918089 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:13:18.642222+05:30
%A Jayshree R. Pansare
%A Aditi Gaikwad
%A Vaishnavi Ankam
%A Priyanka Karne
%A Shikha Sharma
%T Real - Time Text Reader
%J International Journal of Computer Applications
%@ 0975-8887
%V 182
%N 34
%P 42-45
%D 2018
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In most character recognition systems like Optical Character Recognition(OCR), the system may not work well in case of handwritten documents, documents with poor contrast, or when the text and the background are similar in darkness. In some circumstances, the presence of the aforementioned cases leads to poor character recognition. This paper presents a Real Time Text-Reader which works for scanned images and videos. Additionally, the system also extracts text from digital comic images. The system works in 5 phases which are acquirement of the image, pre-processing on image, segmentation, feature extraction, word extraction. It then tags the words into their respective parts of speech categories.

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Index Terms

Computer Science
Information Sciences

Keywords

Optical Character Recognition (OCR) Word extraction Parts of Speech(POS) Tagging Deep Neural Network(DNN)

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