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Text detection method, device, electronic device and computer storage medium

A text detection and text technology, applied in the computer field, can solve problems such as time-consuming, large computing resources, and consumption.

Active Publication Date: 2021-02-05
BEIJING YIZHEN XUESI EDUCATION TECH CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] In view of this, the embodiments of the present application provide a text detection method, device, electronic equipment, and computer storage medium to overcome the defects in the prior art that consume a large amount of computing resources and take a long time when detecting text

Method used

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  • Text detection method, device, electronic device and computer storage medium
  • Text detection method, device, electronic device and computer storage medium
  • Text detection method, device, electronic device and computer storage medium

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Embodiment 1

[0029] Embodiment 1 of the present application provides a text detection method, such as figure 1 as shown, figure 1 It is a flow chart of a text detection method provided in the embodiment of the present application, and the text detection method includes the following steps:

[0030] Step 101, perform feature extraction on the text image to be detected and the gradient image of the text image to be detected to obtain text features, and obtain the text area threshold value map of the text image to be detected, the central area map of the text area, and the vertex offset of the central area according to the text feature prediction Quantitative feature map.

[0031] First of all, it should be noted that the text detection method in the embodiment of the present application is applicable to text detection with various text densities, including but not limited to regular density text, dense density text, sparse density text, especially dense density text. Among them, specific i...

Embodiment 2

[0059] like figure 2 As shown, the second embodiment of the present application is based on the solution of the first embodiment, and step 101 can also be implemented as the following steps 101a-101e.

[0060] Step 101a, acquiring the text image to be detected and the gradient image of the text image to be detected.

[0061] Step 101b, input the text image to be detected and the gradient image into the text detection model.

[0062] In this embodiment, the text detection model includes a first branch and a second branch. Wherein, the first branch includes a first residual network and a first attention layer, and the second branch includes a second residual network and a second attention layer. The first branch is used for feature extraction of the text image to be detected, and the second branch is used for feature extraction of the gradient image. The text detection model also includes a post-processing part, which performs subsequent processing based on the extracted fea...

Embodiment 3

[0079] In this embodiment, based on the text detection method provided in Embodiment 2, before inputting the text image and the gradient image to be detected into the text detection model, the text detection method further includes a process of training the text detection model. Optionally, the text image samples and the gradient image samples corresponding to the text image samples can be obtained; the text detection model is trained by using the text image samples and the gradient image samples.

[0080] When training the text detection model based on text image samples and gradient image samples, the text image samples and gradient image samples are input into the text detection model, and feature extraction and fusion are performed on the text image samples and gradient image samples through the text detection model to obtain the same The text region prediction probability map corresponding to the text image sample, the text region prediction threshold map, the prediction c...

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Abstract

Embodiments of the present application provide a text detection method, device, electronic equipment, and computer storage medium. The text detection method obtains text features by performing feature extraction on the text image to be detected and the gradient image of the text image to be detected. The gradient image can strengthen the text to be detected. Detect the features of the part of the text in the text image to make the extracted features more accurate. According to the text feature prediction, the text area threshold map, the central area map of the text area, and the vertex offset feature map of the central area are obtained; and then according to the original central area Coordinates and the vertex offset of the predicted central region determine the candidate coordinates of the text region; then verify the candidate coordinates based on the relationship between the candidate coordinates and the binary image of the text region, thereby obtaining the text detection result. Through the above method, improve The accuracy of text detection is improved, the calculation amount of text detection is reduced, the computing resources are also saved, and the efficiency and speed of text detection are improved.

Description

technical field [0001] The embodiments of the present application relate to the field of computer technologies, and in particular to a text detection method, device, electronic equipment, and computer storage medium. Background technique [0002] Text detection is a technology that detects text regions in images and marks their bounding boxes. Text detection has a wide range of applications and is a pre-step for many computer vision tasks, such as image search, text recognition, identity authentication, and visual navigation. [0003] The main purpose of text detection is to locate the position of a text line or character in an image. Currently, a popular text detection method is a text detection method based on a sliding window. Based on the idea of ​​general target detection, this method sets a large number of anchor boxes with different aspect ratios and sizes, and uses these anchor boxes as sliding windows to perform convolution operations on the image or on the feature ...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/00G06K9/46G06N3/04G06N3/08
CPCG06N3/08G06V30/413G06V30/414G06V10/44G06V10/56G06N3/045
Inventor 秦勇
Owner BEIJING YIZHEN XUESI EDUCATION TECH CO LTD
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