Open AccessNatural Scene Chinese Character Text Detection Method Based on Improved CTPN
Author(s) -
Wen Zeng,
Qinglin Meng,
Shuqing Zhang
Publication year - 2019
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1314/1/012200
Subject(s) - text detection , character (mathematics) , artificial intelligence , computer science , measure (data warehouse) , image (mathematics) , artificial neural network , pattern recognition (psychology) , natural (archaeology) , natural language processing , scaling , data mining , mathematics , geography , geometry , archaeology
Text detection in natural scenes, due to differences in size, font, line direction, lighting conditions, text weakness and image background complexity, plays an important role in the research field and remains a challenging and important topic. We have improved the CTPN text detection network and changed the Side-refinement detection box to determine the scaling mechanism. And based on the experiment, change the LSTM network to the GRU neural network. In the dataset of Chinese character text game in natural scene released by Meituan, it reached 0.78 F1-Measure, which reached 0.89 and 0.61 F1-Measure on the ICDAR 2013 and 2015 data sets respectively. Compared to the 0.88 and 0.61 F1-Measure in the CTPN article, there is a big improvement.