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Scene Text Detection in Natural Images: A Review

by 1,2, 1,2,*, 1,2, 1,2 and 1,2
1
Chengdu Institute of Computer Applications, Chinese Academy of Sciences, Chengdu 610041, China
2
School of Computer Science and Technology, University of Chinese Academy of Sciences, Beijing 100049, China
*
Author to whom correspondence should be addressed.
Symmetry 2020, 12(12), 1956; https://doi.org/10.3390/sym12121956
Received: 20 October 2020 / Accepted: 20 November 2020 / Published: 26 November 2020
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. View Full-Text
Keywords: scene text detection; natural images; deep learning; detection framework scene text detection; natural images; deep learning; detection framework
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MDPI and ACS Style

Cao, D.; Zhong, Y.; Wang, L.; He, Y.; Dang, J. Scene Text Detection in Natural Images: A Review. Symmetry 2020, 12, 1956. https://doi.org/10.3390/sym12121956

AMA Style

Cao D, Zhong Y, Wang L, He Y, Dang J. Scene Text Detection in Natural Images: A Review. Symmetry. 2020; 12(12):1956. https://doi.org/10.3390/sym12121956

Chicago/Turabian Style

Cao, Dongping; Zhong, Yong; Wang, Lishun; He, Yilong; Dang, Jiachen. 2020. "Scene Text Detection in Natural Images: A Review" Symmetry 12, no. 12: 1956. https://doi.org/10.3390/sym12121956

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