research-article

Text Recognition in UAV Aerial Images

Authors:

ZHIJIE XUAuthors Info & Claims

AIPR '21: Proceedings of the 2021 4th International Conference on Artificial Intelligence and Pattern Recognition

Pages 232 - 238

https://doi.org/10.1145/3488933.3488935

Published: 25 February 2022 Publication History

Abstract

Text recognition in unmanned aerial vehicle (UAV) aerial images is an important branch in the field of machine intelligence, which can provide important discriminative information for subsequent applications. At this stage, text recognition methods have made breakthrough progress, but the recognition of distorted and slanted text is still a challenge. In this case, we construct a text recognition network model with correction module, and propose a new type of UAV aerial image text recognition method. Specifically, the model mainly includes two parts: rectification network and recognition network. The rectification network can be optimized without manual annotation, and it can regularize various distorted and inclined UAV image texts. The recognition network introduces the attention mechanism and improves the decoder to perform bidirectional recognition of the rectified UAV image text. In addition, we verify the effectiveness of the rectification network through a large number of experiments, and prove that the model composed of the rectification network and the recognition network can achieve the optimal recognition performance.

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Cited By

Zhang KWang JZhang XShi YWang T(2023)Time-series Data Modeling Guided by Visual Information2023 IEEE 11th International Conference on Information, Communication and Networks (ICICN)10.1109/ICICN59530.2023.10392643(890-897)Online publication date: 17-Aug-2023
https://doi.org/10.1109/ICICN59530.2023.10392643

Index Terms

Text Recognition in UAV Aerial Images
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision

Index terms have been assigned to the content through auto-classification.

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AIPR '21: Proceedings of the 2021 4th International Conference on Artificial Intelligence and Pattern Recognition

September 2021

715 pages

ISBN:9781450384087

DOI:10.1145/3488933

Copyright © 2021 ACM.

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Published: 25 February 2022

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AIPR 2021

AIPR 2021: 2021 4th International Conference on Artificial Intelligence and Pattern Recognition

September 24 - 26, 2021

Xiamen, China

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Cited By

Zhang KWang JZhang XShi YWang T(2023)Time-series Data Modeling Guided by Visual Information2023 IEEE 11th International Conference on Information, Communication and Networks (ICICN)10.1109/ICICN59530.2023.10392643(890-897)Online publication date: 17-Aug-2023
https://doi.org/10.1109/ICICN59530.2023.10392643

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