Strategies of Traditional Chinese Character Recognition in Streetscape Based on Deep Learning Networks

Sin Wun Svu, Po Chyi Su

研究成果: 書貢獻/報告類型會議論文篇章同行評審

摘要

Text recognition is an important task for extracting information from imagery data. Scene recognition is one of its challenging scenarios since characters may have diversified fonts or sizes, be occluded by other objects and be captured from varying angles or under different light conditions. In contrast to alpha-numerical characters, Traditional Chinese Characters (TCC) receive less attention and the large number of TCC makes it difficult to collect and label enough scene- images. This research aims at developing a set of strategies for TCC recognition. A synthetic dataset using a variety of data augmentation methods is constructed to simulate what may happen in real scenes, including deformations, noise adding and background changes. A segmentation-based spotting scheme is employed to locate the areas of -lines and single characters. The characters can be recognized by the trained model and then linked into meaningful -lines. The experimental results show that the proposed strategies work better in recognizing TCC in streetscape, when compared with existing publicly available tools.

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主出版物標題2021 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2021 - Proceedings
發行者Institute of Electrical and Electronics Engineers Inc.
頁面1494-1498
頁數5
ISBN(電子)9789881476890
出版狀態已出版 - 2021
事件2021 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2021 - Tokyo, Japan
持續時間: 14 12月 202117 12月 2021

出版系列

名字2021 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2021 - Proceedings

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???event.eventtypes.event.conference???2021 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2021
國家/地區Japan
城市Tokyo
期間14/12/2117/12/21

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