Scene Text Detection in Natural Images: A Review
Scene text detection is attracting more and more attention and has become an important topic in machine vision research. With the development of mobile IoT (Internet of things) and deep learning technology, text detection research has made significant progress. This survey aims to summarize and anal...
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Format: | Article |
Language: | English |
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MDPI AG
2020-11-01
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Series: | Symmetry |
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Online Access: | https://www.mdpi.com/2073-8994/12/12/1956 |
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author | Dongping Cao Yong Zhong Lishun Wang Yilong He Jiachen Dang |
author_facet | Dongping Cao Yong Zhong Lishun Wang Yilong He Jiachen Dang |
author_sort | Dongping Cao |
collection | DOAJ |
description | Scene text detection is attracting more and more attention and has become an important topic in machine vision research. With the development of mobile IoT (Internet of things) and deep learning technology, text detection research has made significant progress. This survey aims to summarize and analyze the main challenges and significant progress in scene text detection research. In this paper, we first introduce the history and progress of scene text detection and classify the traditional methods and deep learning-based methods in detail, pointing out the corresponding key issues and techniques. Then, we introduce commonly used benchmark datasets and evaluation protocols and identify state-of-the-art algorithms by comparison. Finally, we summarize and predict potential future research directions. |
first_indexed | 2024-03-10T14:31:49Z |
format | Article |
id | doaj.art-2d536ba84cd84c8081d24ea63e0fc9ad |
institution | Directory Open Access Journal |
issn | 2073-8994 |
language | English |
last_indexed | 2024-03-10T14:31:49Z |
publishDate | 2020-11-01 |
publisher | MDPI AG |
record_format | Article |
series | Symmetry |
spelling | doaj.art-2d536ba84cd84c8081d24ea63e0fc9ad2023-11-20T22:30:50ZengMDPI AGSymmetry2073-89942020-11-011212195610.3390/sym12121956Scene Text Detection in Natural Images: A ReviewDongping Cao0Yong Zhong1Lishun Wang2Yilong He3Jiachen Dang4Chengdu Institute of Computer Applications, Chinese Academy of Sciences, Chengdu 610041, ChinaChengdu Institute of Computer Applications, Chinese Academy of Sciences, Chengdu 610041, ChinaChengdu Institute of Computer Applications, Chinese Academy of Sciences, Chengdu 610041, ChinaChengdu Institute of Computer Applications, Chinese Academy of Sciences, Chengdu 610041, ChinaChengdu Institute of Computer Applications, Chinese Academy of Sciences, Chengdu 610041, ChinaScene text detection is attracting more and more attention and has become an important topic in machine vision research. With the development of mobile IoT (Internet of things) and deep learning technology, text detection research has made significant progress. This survey aims to summarize and analyze the main challenges and significant progress in scene text detection research. In this paper, we first introduce the history and progress of scene text detection and classify the traditional methods and deep learning-based methods in detail, pointing out the corresponding key issues and techniques. Then, we introduce commonly used benchmark datasets and evaluation protocols and identify state-of-the-art algorithms by comparison. Finally, we summarize and predict potential future research directions.https://www.mdpi.com/2073-8994/12/12/1956scene text detectionnatural imagesdeep learningdetection framework |
spellingShingle | Dongping Cao Yong Zhong Lishun Wang Yilong He Jiachen Dang Scene Text Detection in Natural Images: A Review Symmetry scene text detection natural images deep learning detection framework |
title | Scene Text Detection in Natural Images: A Review |
title_full | Scene Text Detection in Natural Images: A Review |
title_fullStr | Scene Text Detection in Natural Images: A Review |
title_full_unstemmed | Scene Text Detection in Natural Images: A Review |
title_short | Scene Text Detection in Natural Images: A Review |
title_sort | scene text detection in natural images a review |
topic | scene text detection natural images deep learning detection framework |
url | https://www.mdpi.com/2073-8994/12/12/1956 |
work_keys_str_mv | AT dongpingcao scenetextdetectioninnaturalimagesareview AT yongzhong scenetextdetectioninnaturalimagesareview AT lishunwang scenetextdetectioninnaturalimagesareview AT yilonghe scenetextdetectioninnaturalimagesareview AT jiachendang scenetextdetectioninnaturalimagesareview |