Computer Engineering and Applications ›› 2021, Vol. 57 ›› Issue (24): 185-191.DOI: 10.3778/j.issn.1002-8331.2007-0098

• Pattern Recognition and Artificial Intelligence • Previous Articles     Next Articles

Text Detection in Natural Scenes Embedded Attention Mechanism

YANG Siqi, YI Yaohua, TANG Ziwei, WANG Xinyu   

  1. Department of Printing and Packaging, Wuhan University, Wuhan 430079, China
  • Online:2021-12-15 Published:2021-12-13



  1. 武汉大学 印刷与包装系,武汉 430079


For missed text detection and detected text deficiency, a text detection method embedded attention mechanism is proposed. Faster-RCNN and Feature Pyramid Network(FPN) are used as the basic framework. Embedded attention mechanism and improved anchor setting, which are designed by text characteristics, are utilized for more accurate text candidate regions. The scope of loss function is reset. The experiment results show that this method can significantly ensure the integrity of detected text information effectively and improve the recall rate and accuracy rate compared with existing methods, which can be exploited for text detection in natural scenes.

Key words: natural scene text detection, feature pyramid network, region proposal network, attention mechanism



关键词: 自然场景文本检测, 特征金字塔网络, 区域建议网络, 注意力机制