UGC Approved Journal no 63975

ISSN: 2349-5162 | ESTD Year : 2014
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Published in:

Volume 6 Issue 6
June-2019
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

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Published Paper ID:
JETIRDC06034


Registration ID:
221834

Page Number

193-196

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Title

Deep Graph Learning Based Approach for Identification of Text in Scene Video

Abstract

Content based analysis, retrieval, searching of scene video has become a key area under computer vision. Apart from indexing and retrieval of videos, demands for video analysis to monitor illegal videos have revolutionized the text detection problem. Because of complex background, low contrast, illuminated, variable font sizes, traditional approach of video based Optical Character Recognition (OCR) system performs satisfactory to detect the text from video. Later, two state-of the-art methods like SIFT and MSER outperformed to detect the text in video but both of these methods fails to detect with complex background. The proposed architecture utilizes the deep graph learning model to detect and identify the scene text from video in two stages. First, regions of similar nature are extracted from the frames by applying undirected graphs. Second, the extracted regions are fed to the learning model to obtain the features which are convolved with internal layers to find the probability of existence of text by calculating the gradients and gray level contrast between text and background. Compared to the conventional detection methods like SIFT and MSER, the detection rate based on deep graph learning can reach 90%. Experimental results show that proposed method is effective compared to two state-of-the-art methods SIFT and MSER.

Key Words

Deep Learning, Graphs, Video, Scene text, CNN, Feature maps

Cite This Article

"Deep Graph Learning Based Approach for Identification of Text in Scene Video ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.193-196, June 2019, Available :http://www.jetir.org/papers/JETIRDC06034.pdf

ISSN


2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

"Deep Graph Learning Based Approach for Identification of Text in Scene Video ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp193-196, June 2019, Available at : http://www.jetir.org/papers/JETIRDC06034.pdf

Publication Details

Published Paper ID: JETIRDC06034
Registration ID: 221834
Published In: Volume 6 | Issue 6 | Year June-2019
DOI (Digital Object Identifier):
Page No: 193-196
Country: Chennai, Tamil Nadu, India .
Area: Engineering
ISSN Number: 2349-5162


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