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Character recognition method and device, electronic equipment and computer readable storage medium

A text recognition and text sequence technology, applied in the field of image processing, can solve the problem of low sequence prediction accuracy

Active Publication Date: 2019-09-06
BEIJING KUANGSHI TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] In view of this, the object of the present invention is to provide a character recognition method, device, electronic equipment and computer-readable storage medium, to alleviate the low sequence prediction accuracy caused by attention shift in the existing image sequence recognition method technical issues

Method used

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  • Character recognition method and device, electronic equipment and computer readable storage medium
  • Character recognition method and device, electronic equipment and computer readable storage medium
  • Character recognition method and device, electronic equipment and computer readable storage medium

Examples

Experimental program
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Embodiment 1

[0032] First, refer to figure 1 An example electronic device 100 for implementing the character recognition method of the embodiment of the present invention will be described.

[0033] Such as figure 1 As shown, the electronic device 100 includes one or more processors 102 and one or more storage devices 104 . Optionally, the electronic device may further include an input device 106, an output device 108, and a camera 110, and these components are interconnected through a bus system 112 and / or other forms of connection mechanisms (not shown). It should be noted that figure 1 The components and structure of the electronic device 100 shown are only exemplary, not limiting, and the electronic device may also have other components and structures as required.

[0034] The processor 102 may be a digital signal processor (Digital Signal Processing, referred to as DSP), a field programmable gate array (Field-Programmable Gate Array, referred to as FPGA), a programmable logic array...

Embodiment 2

[0041] According to an embodiment of the present invention, an embodiment of a character recognition method is provided. It should be noted that the steps shown in the flowcharts of the drawings can be executed in a computer system such as a set of computer-executable instructions, and, although A logical order is shown in the flowcharts, but in some cases the steps shown or described may be performed in an order different from that shown or described herein.

[0042] figure 2 is a flow chart of a character recognition method according to an embodiment of the present invention, such as figure 2 As shown, the method includes the following steps:

[0043] Step S202, acquiring an image to be detected.

[0044] In this embodiment, the image to be detected may be an image captured by the camera 110 in the electronic device described in Embodiment 1 above, or may be received from other electronic devices.

[0045] Step S204, extracting feature information of the image to be det...

Embodiment 3

[0116] The embodiment of the present invention also provides a character recognition device, the character recognition device is mainly used to implement the character recognition method provided in the above-mentioned content of the embodiment of the present invention, and the character recognition device provided by the embodiment of the present invention will be described in detail below.

[0117] Figure 7 is a schematic diagram of a character recognition device according to an embodiment of the present invention, such as Figure 7 As shown, the character recognition device mainly includes an acquisition unit 10, an extraction unit 20 and a determination unit 30, wherein:

[0118] An acquisition unit 10, configured to acquire an image to be detected;

[0119] The extraction unit 20 is used to extract the feature information of the image to be detected by using the fully convolutional neural network trained by the two-dimensional CTC model to obtain the first feature infor...

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Abstract

The invention provides a character recognition method and device, electronic equipment and a computer readable storage medium, and the method comprises the steps: obtaining a to-be-detected image, extracting the feature information of the to-be-detected image through a full convolutional neural network trained by adopting a two-dimensional CTC model, and obtaining first feature information; wherein the first feature information comprises at least one of the following: representing a first character distribution probability that each feature point in first two-dimensional spatial feature distribution of the to-be-detected image belongs to a first character sequence; representing a first path transition probability in a height dimension in the first two-dimensional spatial feature distribution; wherein each feature point representing the first two-dimensional spatial feature distribution is a first initial path probability of an initial feature point on a first path; and determining a first character sequence in the to-be-detected image by using the first feature information of the to-be-detected image. According to the invention, the technical problem of low sequence prediction accuracy caused by attention offset in the existing image sequence identification method is relieved.

Description

technical field [0001] The present invention relates to the technical field of image processing, in particular to a character recognition method, device, electronic equipment and computer-readable storage medium. Background technique [0002] Text recognition in natural scenes, hereinafter referred to as scene text recognition, refers to the technology of using computer algorithms to identify the content of text in natural scene pictures. It is widely used in many fields such as automatic driving, visually impaired assistance, and identity authentication. Different from text recognition in scanned documents, text recognition in natural scenes faces greater challenges: complex natural backgrounds, uncertain text directions and arrangements, and a large number of color changes, etc., all of which make text recognition in natural scenes difficult. The recognition accuracy and implementation difficulty are much higher than the recognition of scanned documents. [0003] In the s...

Claims

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Application Information

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IPC IPC(8): G06K9/32G06K9/34G06K9/62G06N3/04
CPCG06V20/62G06V30/153G06N3/045G06F18/214
Inventor 万昭祎刘毅博谢锋明姚聪杨沐
Owner BEIJING KUANGSHI TECH
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