Non-invasive camera shooting reading method and system based on deep learning

A non-invasive, deep learning technology, applied in the field of image recognition, can solve problems such as low flexibility, limited data, production visualization management dependent on production equipment, etc., and achieve the effect of improving decision-making efficiency

Pending Publication Date: 2020-09-11
HANGZHOU WEIMING XINKE TECH CO LTD +1
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The present invention proposes a non-invasive camera reading method and system based on deep learning, which aims to solve the problems in the prior art that the production visualization management of industrial computer systems depends on production equipment, has low flexibility and limited data

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  • Non-invasive camera shooting reading method and system based on deep learning
  • Non-invasive camera shooting reading method and system based on deep learning
  • Non-invasive camera shooting reading method and system based on deep learning

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Embodiment 1

[0051] In order to better illustrate the non-intrusive imaging and reading method based on deep learning in the embodiment of the present application, firstly, the non-invasive technology, imaging and reading technology, image processing technology, character recognition technology and image classification technology adopted in the embodiment of the application to describe.

[0052] Regarding non-intrusive technology, non-intrusive refers to the technology to obtain the required data without modifying the original operating system. The typical feature of this technology is that there is no need to install auxiliary software on the host computer, and no need to install device drivers. In the embodiment of the present application, the direct reading of the memory data of the industrial computer is avoided through the non-invasive technology, thus avoiding the risk of paralysis of the industrial computer. To control the display interface of the industrial computer, and use it as...

Embodiment 2

[0146] This embodiment provides a non-invasive camera reading system based on deep learning. For details not disclosed in the non-invasive camera reading system based on deep learning in this embodiment, please refer to the depth-based A non-invasive camera-reading method for learning.

[0147] Figure 11 A schematic structural diagram of a non-invasive imaging reading system based on deep learning according to an embodiment of the present application is shown. Such as Figure 11 As shown, the non-invasive camera reading system based on deep learning in the embodiment of the present application includes an interface acquisition module 10 and an interface identification module 20 .

[0148] Such as Figure 11 As shown, the specific structure of the non-invasive camera reading system based on deep learning is as follows:

[0149] The interface acquisition module 10 is configured to capture an interface image of the industrial control system by taking a camera.

[0150] The ...

Embodiment 3

[0167] This embodiment provides a non-invasive camera reading terminal. For details not disclosed in the non-invasive camera reading terminal of this embodiment, please refer to the non-invasive camera reading based on deep learning in other embodiments. methods and systems.

[0168] Figure 14 A schematic structural diagram of a non-intrusive imaging and reading terminal according to an embodiment of the present application is shown. Such as Figure 14 As shown, the terminal provided in this embodiment includes: a memory 301, a processor 302, and a computer program, wherein the computer program is stored in the memory 301 and is configured to be executed by the processor 302 to implement any embodiment provided Non-invasive camera reading method based on deep learning.

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Abstract

The embodiment of the invention provides a non-invasive camera shooting reading method and system based on deep learning. The method comprises: firstly, obtaining an interface image of an industrial control system through camera shooting; and then, performing character recognition according to the interface image to obtain a key data field recognition result, and / or performing image classificationaccording to the interface image to obtain a classification recognition result. On the premise that production equipment does not need to be invaded, real-time acquisition and visual management of key production data of the industrial personal computer system can be flexibly achieved without limitation. In the application of manufacturing enterprises, the step of manual copying by workers is omitted, the workers can be helped to better manage the industrial personal computer, the data result can also assist managers in improving the decision-making efficiency, and a guarantee is provided forinformatization of the enterprises and intelligent decision making of big data.

Description

technical field [0001] The present application belongs to the technical field of image recognition, and in particular relates to a non-intrusive image reading method and system based on deep learning. Background technique [0002] In the vast majority of manufacturing enterprises, the various links of the production process are complex, the safety protection requirements are high, and the production equipment is highly precise. Therefore, it is necessary to collect and analyze a large amount of process data and energy consumption data generated in the production process in real time, and at the same time, it is necessary to coordinate optimization of multiple control subsystems. In the current situation, most enterprises use manual entry or on-site statistical analysis, and then submit the workers' records and statistical analysis results to the enterprise managers, so that the enterprise managers can improve the efficiency of management decision-making. However, because th...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/34G06F9/451G06K9/62
CPCG06F9/451G06V30/153G06F18/241G06F18/25
Inventor 王建凯许鸿坤陈曦麻志毅
Owner HANGZHOU WEIMING XINKE TECH CO LTD
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