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Reseach Article

Hybrid Approach to Extract Text in Natural Scene Images

by Kumuda T., Basavaraj L.
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 142 - Number 10
Year of Publication: 2016
Authors: Kumuda T., Basavaraj L.
10.5120/ijca2016909937

Kumuda T., Basavaraj L. . Hybrid Approach to Extract Text in Natural Scene Images. International Journal of Computer Applications. 142, 10 ( May 2016), 18-22. DOI=10.5120/ijca2016909937

@article{ 10.5120/ijca2016909937,
author = { Kumuda T., Basavaraj L. },
title = { Hybrid Approach to Extract Text in Natural Scene Images },
journal = { International Journal of Computer Applications },
issue_date = { May 2016 },
volume = { 142 },
number = { 10 },
month = { May },
year = { 2016 },
issn = { 0975-8887 },
pages = { 18-22 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume142/number10/24932-2016909937/ },
doi = { 10.5120/ijca2016909937 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:44:37.031692+05:30
%A Kumuda T.
%A Basavaraj L.
%T Hybrid Approach to Extract Text in Natural Scene Images
%J International Journal of Computer Applications
%@ 0975-8887
%V 142
%N 10
%P 18-22
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Text Extraction from natural scene images has been done with various methodologies. Most of the existing systems mainly use color and edges for detecting the text. We propose a two stage hybrid text extraction approach by combining texture and CC-based information. Text in the image is detected and localized using first and second order statistical texture features. In the next stage CC extraction is used to segment candidate text components from the localized text region. Finally morphological operations and heuristic filters are used to filter out non text components. Experimental results show that the proposed approach detects, localizes and extracts text from natural scene images efficiently and also can handle variations in size, fonts and orientation.

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Index Terms

Computer Science
Information Sciences

Keywords

Natural scene images statistical features text localization text extraction connected component morphological operation texture analysis heuristic filters.