Text detection method and device, medium and electronic equipment

Abstract

The invention relates to a text detection method and device, a medium and electronic equipment. The method is applied to a Mask RCNN model, a region suggestion network RPN in the model is replaced by a segmentation network, and the method comprises the following steps: obtaining a first feature map of an original image containing a text; obtaining a first segmentation result of the first feature map through a segmentation network, wherein the first segmentation result comprises a plurality of polygon frames surrounding the text region; performing post-processing on the plurality of polygonal frames to obtain a plurality of corrected rectangular frames; extracting second feature maps of the plurality of corrected rectangular frames, and multiplying the plurality of second feature maps with corresponding local feature maps in the first feature map to obtain a third feature map; acquiring a detection result and a second segmentation result of the third feature map through the model, wherein the detection result comprises a plurality of candidate rectangular frames, and the second segmentation result comprises the feature map surrounding the text area in each candidate rectangular frame. According to the embodiment of the invention, distorted and inclined texts in the image can be accurately detected and recognized.

Description

technical field [0001] The embodiments of the present disclosure relate to the technical field of image processing, and in particular, to a text detection method, a text detection device, and a computer-readable storage medium and electronic equipment for implementing the text detection method. Background technique [0002] At present, in the face of image data, how to efficiently and automatically obtain useful text information from images has become a research hotspot. [0003] In related technologies, the image text detection scheme adopts a target detection two-stage network such as Faster RCNN (Faster Region Convolutional Neural Networks), which can improve the efficiency of automatic text information detection to a certain extent. [0004] However, the current image text detection scheme fails to consider the text tilt and distortion of the text in the image, so the accuracy and efficiency of image text detection and recognition in the text tilt, distortion and other s...

AI Technical Summary

Problems solved by technology

[0004] However, the current image text detection scheme fails to consider the text tilt and distortion of the text in the image, so the accuracy and efficiency of image text detection and recognition in the text tilt, distortion and other scenarios are low.

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