Scene Text Detection Based on the Connection of the Characters
In recent years,the research direction of scene text detection is more and more extensive.Thanks to the develop-ment of deep convolutional network and image segmentation technology,scene text detector can generate a variety of text boxes for the curved text of any shape in the image.In addition,the text in the scene image sometimes shows the characteristics of too small text,too extreme aspect ratio and so on.Under the circumstance of deep convolution and finite receptive field,the network is easy to lose the feature information of small text and cannot obtain the complete feature of long text.Aiming at these two difficulties,this pa-per designs a scene text detector based on character connection,and uses the improved AFF module to fuse local features with glob-al features to make the network more sensitive to small text targets and avoid the problem of small text missing detection.The net-work output character area and character gap are scored,and text lines are connected according to the connection property between characters,so that the network can detect arbitrary long text.Since the general text detection dataset lacks character-level annota-tions,weakly supervised learning strategy is used to generate character-level pseudo-labels,and character-level synthetic dataset is made to make up for the deficiency of weakly supervised learning,so that the network can better learn the features of scene text.Experimental results show that the method has excellent performance on general dataset ICDAR2015 and MSRA-TD500.
scene textattentional feature fusionweakly supervised learningconnection of the characters
万方数据
维普
