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Text detection method, electronic equipment and computer readable medium

A text detection and detection technology, which is applied in the computer field, can solve the problems of large amount of calculation, long time consumption, and large consumption of computing resources, so as to reduce the amount of data calculation, reduce the amount of data, and improve the detection speed and efficiency.

Inactive Publication Date: 2020-09-11
BEIJING YIZHEN XUESI EDUCATION TECH CO LTD
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  • 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

Method used

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  • Text detection method, electronic equipment and computer readable medium
  • Text detection method, electronic equipment and computer readable medium
  • Text detection method, electronic equipment and computer readable medium

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0020] Referring to FIG. 1 , it shows a flowchart of steps of a text detection method according to Embodiment 1 of the present invention.

[0021] The text detection method of the present embodiment comprises the following steps:

[0022] Step S102: Perform feature extraction and segmentation on the text image to be detected, and obtain a text region probability map of the text image to be detected.

[0023] The solutions of the embodiments of the present invention are 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, the specific indicators for determining whether a certain text is a dense text can be appropriately set by those skilled in the art according to the actual situation, including but not limited to: according to the spacing between texts (such as spacing less than 2 points, etc.), according to the text within the unit range ...

Embodiment 2

[0053] refer to figure 2 , shows a schematic flowchart of a text detection method according to Embodiment 2 of the present invention.

[0054] The text detection method of the present embodiment adopts such as Figure 1D The neural network model implementation shown in , the text detection method includes the following steps:

[0055] Step S202: Input the text image to be detected into the Resnet18 network.

[0056] In this embodiment, the Resnet18 network, as a part of the PAN, is a trained network through which the features of the input image can be extracted, and the features of a certain channel form the feature map of the channel.

[0057] Step S204: Perform feature extraction through the Resnet18 network.

[0058] In order to distinguish it from the subsequent feature extraction, the feature extraction in this step is marked as extraction feature 1, through which features such as texture, edge, corner and semantic information of the image can be extracted.

[0059] ...

Embodiment 3

[0080] image 3 It is the hardware structure of the electronic equipment in the third embodiment of the present invention; as image 3 As shown, the electronic device may include: a processor (processor) 301 , a communication interface (Communications Interface) 302 , a memory (memory) 303 , and a communication bus 304 .

[0081] in:

[0082] The processor 301 , the communication interface 302 , and the memory 303 communicate with each other through the communication bus 304 .

[0083] The communication interface 302 is used for communicating with other electronic devices or servers.

[0084] The processor 301 is configured to execute the program 305, and specifically, may execute relevant steps in the above text detection method embodiment.

[0085] Specifically, the program 305 may include program codes including computer operation instructions.

[0086] The processor 301 may be a central processing unit CPU, or an ASIC (Application Specific Integrated Circuit), or one o...

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Abstract

The embodiment of the invention discloses a text detection method, electronic equipment and a computer readable medium, and the text detection method comprises the steps: carrying out the feature extraction and segmentation of a to-be-detected text image, and obtaining a text region probability graph of the to-be-detected text image; determining a text region binary image of the to-be-detected text image according to the text region probability graph; extracting edge information of the text area binary image to obtain a text area edge image; performing connected domain detection on the text area edge graph, and obtaining a minimum enclosing rectangle of the text area according to a detection result; and obtaining a text detection result of the to-be-detected text image according to the minimum bounding rectangle. According to the method of the invention, the speed and efficiency of text detection, especially dense text detection, are improved.

Description

technical field [0001] The embodiments of the present invention relate to the field of computer technology, and in particular, to a text detection method, electronic equipment, and a computer-readable 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 feature m...

Claims

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Application Information

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IPC IPC(8): G06K9/32G06K9/34G06N3/04
CPCG06V20/62G06V30/153G06N3/045
Inventor 秦勇李兵张子浩
Owner BEIJING YIZHEN XUESI EDUCATION TECH CO LTD
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