Method and device for recognizing text in image, electronic equipment, and storage medium

Abstract

The invention discloses a method and device for recognizing text in an image, electronic equipment, and a computer readable storage medium. The scheme performs end-to-end recognition of text in an image through a network model of multi-layer superposition. The scheme includes: a space separable convolution operation of the image is carried out layer by layer through a multi-layer mode; convolutionfeatures extracted from the space separable convolution operation are fused to low layers mapped by layer superposition; the low layers are mapped to high layers of output convolution features; Obtaining global features from the bottom layer of the performing spatially separable convolution operation; Candidate region detection and region filtering parameter prediction of text in the image are carried out through global features, and pooling features corresponding to the detected text regions are obtained. The pooling feature is propagated backward to the recognition branch network layer thatperforms the character recognition operation, and the character sequence marked by the text area is output by the recognition branch network layer. The scheme saves the training time of the model andimproves the recognition accuracy.

Description

technical field [0001] The invention relates to the technical field of image processing, in particular to a text recognition method and device in an image, electronic equipment, and a computer-readable storage medium. Background technique [0002] In the field of computer image processing, text recognition refers to allowing the computer to automatically determine which character in the image belongs to the character library. The character library is established by people in advance and usually contains the most commonly used characters in real life. [0003] The recognition of text in an image usually builds two models, one model is used to find the location of the text in a natural scene image containing text, and then crops the text area from the image. Another model is used to identify the specific character content of the text area. Specifically, a large number of sample images containing different characters are obtained as a training set, and these sample images are ...

AI Technical Summary

Problems solved by technology

[0005] In order to solve the problems in the related art that the training of the character classifier and the training of the text locator need to be carried out separately, the workload of the model training is relatively large, and the recognition accuracy is not high, the present invention provides a text recognition method in an image

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