In the process of processing related network pictures, the traditional system is difficult to extract features and it makes the pictures recognition rate becoming inefficiency. In this study, we propose a module based on spatial transformation and dense neural network method to recognize the images, extract text feature, and transform the parameter about sensitive text pictures. The module using the deep GRU and CTC to mark characteristics of sequence prediction information, and serialization of dealing with the text can better improve the ability of wider text and fuzzy text information. Experimental results show that the recognition accuracy of the model in Caffe-OCR Chinese composite data set and CTW data set is 87.0% and 90.3% respectively, and the average recognition time reaches 26.3 ms/graph.