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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 the problems of reducing text detection speed, consuming large computing resources, and large amount of calculation.

Active Publication Date: 2021-04-09
BEIJING YIZHEN XUESI EDUCATION TECH CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] However, this method requires a large amount of calculation, which not only consumes a lot of computing resources, but also takes a long time, which reduces the speed of text detection

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

Examples

Experimental program
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Effect test

Embodiment 1

[0033] 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:

[0034] Step S101 , perform feature extraction on the text image to be detected, and obtain a text region threshold map corresponding to the text image to be detected, a text region boundary point probability map, and coordinate offsets between text region boundary points and adjacent boundary points.

[0035] 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 indicators for determining whether a certain text is a dense text can be appropriately set by those...

Embodiment 2

[0046] Embodiment 2 of the present application is based on the solution of Embodiment 1. Optionally, in an embodiment of the present application, step S103 may be implemented as the following step S103a and step S103b.

[0047] Exemplarily, in step S103a, an AND operation is performed on the binary image of the text frame and the binary image of the boundary points of the text region to obtain the boundary image of the text region.

[0048] Wherein, the text area boundary map is used to represent the boundary points located on the frame of the text area. Through the AND operation, effective pixels in the binary image of the boundary points of the text region can be retained, or noise pixels in the binary image of the boundary points of the text region can be filtered out.

[0049] Optionally, in one embodiment of the present application, step S103a is implemented in the following manner: determine the pixel points corresponding to the pixel points representing the text frame i...

Embodiment 3

[0070] Embodiment 3 of the present application is based on the solutions of Embodiment 1 and Embodiment 2, wherein step S101 can also be implemented as the following steps S101a-step S101d.

[0071] Step S101a, performing first text feature extraction on the text image to be detected.

[0072] In the embodiment of the present application, when feature extraction is performed on the text image to be detected, the text image to be detected is input into the residual network part (such as the Resnet network), and the first text feature is extracted, and the texture, edge, corner and Features such as semantic information, which are represented by 4 sets of feature maps of different sizes. Take the text image to be detected as the original image, and the Resnet network extracts the features of the original image as an example. The Resnet18 network is constructed by connecting four blocks in series. Each block includes several layers of convolution operations. The output of the firs...

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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 includes: performing feature extraction on a text image to be detected, and obtaining a text region threshold map and a text region boundary corresponding to the text image to be detected. The point probability map, and the coordinate offset between the boundary point of the text area and the adjacent boundary point; binarize the threshold value map of the text area and the probability map of the boundary point of the text area respectively, and obtain the corresponding text border binary image and text area Boundary point binary image; according to the text frame binary image and the text area boundary point binary image, determine the boundary point coordinate set; according to the boundary point coordinate set, and the coordinate offset between the text area boundary point and the adjacent boundary point, get The coordinates of the boundary points of the text area are used to obtain the text detection result, which improves the accuracy of the text detection; through the above method, the efficiency and speed of the 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 different sizes, and uses these anchor boxes as sliding windows to perform convolution operations on the image or the f...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/32G06K9/20G06K9/00G06K9/38
CPCG06V30/40G06V10/22G06V20/62G06V10/28
Inventor 杨家博秦勇
Owner BEIJING YIZHEN XUESI EDUCATION TECH CO LTD
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