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

A text recognition and text sequence technology, applied in the field of image processing, can solve the problems of low sequence prediction accuracy and achieve the effect of alleviating the low sequence prediction accuracy and improving recognition accuracy

Active Publication Date: 2021-08-10
BEIJING KUANGSHI TECH CO LTD
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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, device, electronic device and computer-readable storage medium
  • Character recognition method, device, electronic device and computer-readable storage medium
  • Character recognition method, device, electronic device and computer-readable storage medium

Examples

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Embodiment 1

[0033] First, refer to figure 1 An example electronic device 100 for implementing the character recognition method of the embodiment of the present invention is described.

[0034] like 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 also include an input device 106, an output device 108, and a camera 110, these components being interconnected by a bus system 112 and / or other form of connection mechanism (not shown). It should be noted that figure 1 The illustrated components and structures of the electronic device 100 are only exemplary and not limiting, and the electronic device may also have other components and structures as desired.

[0035] The processor 102 may adopt a digital signal processor (Digital Signal Processing, DSP for short), a Field-Programmable Gate Array (FPGA for short), a programmable logic array (Programmable logic arrays, PLA for short), and ...

Embodiment 2

[0042] According to an embodiment of the present invention, an embodiment of a method for character recognition is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings may 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 steps shown or described may be performed in an order different from that herein.

[0043] figure 2 is a flowchart of a method for character recognition according to an embodiment of the present invention, such as figure 2 As shown, the method includes the following steps:

[0044] Step S202, acquiring an image to be detected.

[0045] In this embodiment, the to-be-detected image may be the image captured by the camera 110 in the electronic device described in the first embodiment, or may be received from other electronic devices.

[0046] Step S204 , extracting the feature information of the image to be ...

Embodiment 3

[0117] An embodiment of the present invention further provides a character recognition device, which is mainly used to execute the character recognition method provided by the above content of the embodiment of the present invention. The text recognition device provided by the embodiment of the present invention will be described in detail below.

[0118] 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:

[0119] an acquisition unit 10, configured to acquire an image to be detected;

[0120] The extraction unit 20 is used for extracting the feature information of the image to be detected by adopting the full convolutional neural network after the training of the two-dimensional CTC model to obtain the first feature information;

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Abstract

The invention provides a character recognition method, device, electronic equipment and computer-readable storage medium, the method comprising: acquiring an image to be detected, and extracting features of the image to be detected by using a fully convolutional neural network trained by a two-dimensional CTC model Information to obtain the first feature information; the first feature information includes at least one of the following: the first character distribution probability that each feature point in the first two-dimensional spatial feature distribution of the image to be detected belongs to the first character sequence; The first path transition probability on the height dimension in the three-dimensional space feature distribution; each feature point representing the first two-dimensional space feature distribution is the first initial path probability of the initial feature point on the first path; using the first path probability of the image to be detected The feature information determines the first character sequence in the image to be detected. The present application alleviates the technical problem of low sequence prediction accuracy caused by attention shift in existing image sequence recognition methods.

Description

technical field [0001] The present invention relates to the technical field of image processing, and in particular, to a character recognition method, apparatus, electronic device and computer-readable storage medium. Background technique [0002] The recognition of text in natural scenes, hereinafter referred to as scene text recognition, refers to the technology that uses computer algorithms to identify the content of text in natural scene pictures. 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, 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 prior art, the widely used image-based sequence recognition method is the attention-based model. Among these att...

Claims

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Application Information

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Patent Type & Authority Patents(China)
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 CO LTD
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