Text detection based on enhanced receptive field and improved loss function

The current mainstream text detection algorithms have significant effect on multi-directional text detection, but they are not good at detection of curve text. A text detection algorithm based on enhanced receptive field and improved loss function is proposed in this paper, which is also suitable for curve and arbitrary text. The algorithm is further improved based on TextSnake network. Improved ASPP network is added to increase receptive field to obtain higher level semantic information in the deep network, and feature fusion is performed layer by layer to improve the detection accuracy in the complex background. In the part of loss function, the weighted Focal Loss is used to improve the loss of pixels difficult in the detection process. The algorithm is tested on the Total-Text datesets and ICDAR2015 datesets, and the experimental results show that the algorithm performs well in both precision and F-score.