A review of natural scene text detection methods

Lingqian Yang, Daji Ergu*, Ying Cai*, Fangyao Liu, Bo Ma

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

12 Citations (Scopus)

Abstract

Natural scene text detection has an important role to play in getting textual information from natural scenes. With the continuous development of deep learning, natural scene text detection methods are emerging and achieving better results on detection tasks. In this paper, analysis, and summary of the current stage of deep learning-based text algorithms for natural scenes, can be divided into two types: region of the proposal and semantic segmentation, and the content of these two series of related algorithms is described. Secondly, a publicly available dataset and detection performance metrics for scene text detection are presented. Ultimately, the research in scene text detection is summarized and looked forward to in the hope of providing new research directions for subsequent algorithms.

Original languageEnglish
Pages (from-to)1458-1465
Number of pages8
JournalProcedia Computer Science
Volume199
DOIs
Publication statusPublished - 2021
Externally publishedYes
Event8th International Conference on Information Technology and Quantitative Management, ITQM 2020 and 2021 - Chengdu, China
Duration: 9 Jul 202111 Jul 2021

Keywords

  • Deep learning
  • Nature scenes
  • Text detection

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