A Method of Effective Text Extraction for Complex Video Scene

A Method of Effective Text Extraction for Complex Video Scene

Text information contains important information for video analysis, indexing, and retrieval. Effective and efficient text extraction has been a challenging topic in recent years. Focusing on this issue, a text extraction method for complex video scene is proposed in this paper. Multiframe corner mat...

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Main Authors: Zhe Guo, Yuan Li, Yi Wang, Shu Liu, Tao Lei, Yangyu Fan
Format: Article
Language:English
Published: Hindawi Limited 2016-01-01
Series:Mathematical Problems in Engineering
Online Access:http://dx.doi.org/10.1155/2016/2187647
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spelling doaj-cfc97c6fa6df4a19ad4c9d79498bb6112020-11-24T21:06:37ZengHindawi LimitedMathematical Problems in Engineering1024-123X1563-51472016-01-01201610.1155/2016/21876472187647A Method of Effective Text Extraction for Complex Video SceneZhe Guo0Yuan Li1Yi Wang2Shu Liu3Tao Lei4Yangyu Fan5School of Electronics and Information, Northwestern Polytechnical University, Xi’an 710072, ChinaSchool of Electronics and Information, Northwestern Polytechnical University, Xi’an 710072, ChinaSchool of Electronics and Information, Northwestern Polytechnical University, Xi’an 710072, ChinaSchool of Electronics and Information, Northwestern Polytechnical University, Xi’an 710072, ChinaSchool of Computer Science, Northwestern Polytechnical University, Xi’an 710072, ChinaSchool of Electronics and Information, Northwestern Polytechnical University, Xi’an 710072, ChinaText information contains important information for video analysis, indexing, and retrieval. Effective and efficient text extraction has been a challenging topic in recent years. Focusing on this issue, a text extraction method for complex video scene is proposed in this paper. Multiframe corner matching and heuristic rules are combined together to detect the text region candidates, which solves the issue of Harris corner filtration for complex video scene and also improves the detection accuracy using multiframe fusion. Local texture description is then used for similarity evaluation judged by SVM. Experimental results for 4 different types of 395-frame video images show the effectiveness of the proposed method compared with 5 existing text extraction methods.http://dx.doi.org/10.1155/2016/2187647
collection DOAJ
language English
format Article
sources DOAJ
author Zhe Guo
Yuan Li
Yi Wang
Shu Liu
Tao Lei
Yangyu Fan
spellingShingle Zhe Guo
Yuan Li
Yi Wang
Shu Liu
Tao Lei
Yangyu Fan
A Method of Effective Text Extraction for Complex Video Scene
Mathematical Problems in Engineering
author_facet Zhe Guo
Yuan Li
Yi Wang
Shu Liu
Tao Lei
Yangyu Fan
author_sort Zhe Guo
title A Method of Effective Text Extraction for Complex Video Scene
title_short A Method of Effective Text Extraction for Complex Video Scene
title_full A Method of Effective Text Extraction for Complex Video Scene
title_fullStr A Method of Effective Text Extraction for Complex Video Scene
title_full_unstemmed A Method of Effective Text Extraction for Complex Video Scene
title_sort method of effective text extraction for complex video scene
publisher Hindawi Limited
series Mathematical Problems in Engineering
issn 1024-123X
1563-5147
publishDate 2016-01-01
description Text information contains important information for video analysis, indexing, and retrieval. Effective and efficient text extraction has been a challenging topic in recent years. Focusing on this issue, a text extraction method for complex video scene is proposed in this paper. Multiframe corner matching and heuristic rules are combined together to detect the text region candidates, which solves the issue of Harris corner filtration for complex video scene and also improves the detection accuracy using multiframe fusion. Local texture description is then used for similarity evaluation judged by SVM. Experimental results for 4 different types of 395-frame video images show the effectiveness of the proposed method compared with 5 existing text extraction methods.
url http://dx.doi.org/10.1155/2016/2187647
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