PSENet-based efficient scene text detection

EURASIP Journal on Advances in Signal Processing

Guanglong Liao¹  Zhongjie Zhu¹  Tingna Liu¹  Yongqiang Bai¹  Zhibo Xie¹ 

[1] Ningbo Key Lab of Digital Signal Processing, Zhejiang Wanli University, 315100, Ningbo, China;

关键词: Scene text detection;    PSENet;    Mixed Pooling Module;   

DOI  :  10.1186/s13634-021-00808-5

来源: Springer

【 摘 要 】

Text detection is a key technique and plays an important role in computer vision applications, but efficient and precise text detection is still challenging. In this paper, an efficient scene text detection scheme is proposed based on the Progressive Scale Expansion Network (PSENet). A Mixed Pooling Module (MPM) is designed to effectively capture the dependence of text information at different distances, where different pooling operations are employed to better extract information of text shape. The backbone network is optimized by combining two extensions of the Residual Network (ResNet), i.e., ResNeXt and Res2Net, to enhance feature extraction effectiveness. Experimental results show that the precision of our scheme is improved more than by 5% compared with the original PSENet.

【 授权许可】

CC BY