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 language | English |
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Pages (from-to) | 1458-1465 |
Number of pages | 8 |
Journal | Procedia Computer Science |
Volume | 199 |
DOIs | |
Publication status | Published - 2021 |
Externally published | Yes |
Event | 8th International Conference on Information Technology and Quantitative Management, ITQM 2020 and 2021 - Chengdu, China Duration: 9 Jul 2021 → 11 Jul 2021 |
Keywords
- Deep learning
- Nature scenes
- Text detection