CN113343911A - Image identification method - Google Patents
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- CN113343911A CN113343911A CN202110725394.7A CN202110725394A CN113343911A CN 113343911 A CN113343911 A CN 113343911A CN 202110725394 A CN202110725394 A CN 202110725394A CN 113343911 A CN113343911 A CN 113343911A
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Abstract
The invention relates to the technical field of image recognition, in particular to an image recognition method which can shorten the recognition time of an image, simplify the recognition mode and be simply applied to some specific scenes; the method comprises the following steps: s1: acquiring an initial state of an image, marking the initial state as an image model, and marking the number of bytes of pixels of the image model as a model parameter; s2: acquiring the image again, and comparing the number of bytes of the pixel of the image acquired again with the model parameter; s3: when the difference value between the obtained pixel byte number and the model parameter is larger than a certain value, judging that the current scene changes; and when the difference value between the obtained pixel byte number and the model parameter is less than or equal to a certain value, judging that the current scene is not changed.
Description
Technical Field
The invention relates to the technical field of image recognition, in particular to an image recognition method.
Background
With the continuous development of the mobile internet technology and the internet of things technology and the change and improvement of the living idea of people, the image recognition technology has been widely applied, and has wide application prospects in various fields such as safety, finance, man-machine interaction, information, education and the like.
Disclosure of Invention
Technical problem to be solved
Aiming at the defects of the prior art, the invention provides the image identification method which shortens the image identification time, simplifies the identification mode and is simply applied to some specific scenes.
(II) technical scheme
In order to achieve the purpose, the invention provides the following technical scheme: an image recognition method includes:
s1: acquiring an initial state of an image, marking the initial state as an image model, and marking the number of bytes of pixels of the image model as a model parameter;
s2: acquiring the image again, and comparing the number of bytes of the pixel of the image acquired again with the model parameter;
s3: when the difference value between the obtained pixel byte number and the model parameter is larger than a certain value, judging that the current scene changes; and when the difference value between the obtained pixel byte number and the model parameter is less than or equal to a certain value, judging that the current scene is not changed.
Preferably, a contrast value is preset, and in step S3, the difference value between the number of bytes of the pixel and the model parameter is compared with the contrast value.
Preferably, in step S3, after the comparison between the acquired number of bytes of pixels and the model parameter is finished, the process returns to step S2 again.
Preferably, in step S1, the image initial state can be manually updated.
(III) advantageous effects
Compared with the prior art, the invention provides an image identification method, which has the following beneficial effects: according to the method, the number of bytes of the pixel is compared with the number of memory capacity of the pixel to judge whether the current scene changes, and compared with the conventional image recognition technology, the method shortens the recognition time of the image, simplifies the recognition mode, is simple to apply in some specific scenes, and is more convenient to use.
Drawings
FIG. 1 is a flow chart of the operation of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments that can be derived by one of ordinary skill in the art from the embodiments given herein are intended to be within the scope of the present invention.
Referring to fig. 1, an image recognition method according to the present invention includes:
s1: acquiring an initial state of an image, marking the initial state as an image model, and marking the number of bytes of pixels of the image model as a model parameter;
in the embodiment of the invention, the initial state of the image can be manually updated;
for example, in a specific embodiment, the current environmental situation is obtained, the obtained graph is labeled as an image model, and the number of bytes of the obtained graph is labeled as a model parameter, and then the process proceeds to step S1, and when the number of the intrinsic items in the environment increases or decreases, the current environmental situation can be obtained again through manual updating.
S2: acquiring the image again, and comparing the number of bytes of the pixel of the image acquired again with the model parameter;
in this embodiment of the present invention, for example, in a specific embodiment, an environmental image that needs to be determined is obtained, the number of bytes of pixels of the obtained image is compared with the model parameter, an absolute value of a difference value between the number of bytes of the obtained image and the model parameter is selected, and then the process proceeds to step S3.
S3: when the difference value between the obtained pixel byte number and the model parameter is larger than a certain value, judging that the current scene changes; when the difference value between the obtained pixel byte number and the model parameter is less than or equal to a certain value, judging that the current scene is not changed;
in the embodiment of the invention, a comparison value is preset, the difference value between the number of bytes of the pixel and the model parameter is compared with the comparison value, and after the comparison between the number of bytes of the pixel and the model parameter is finished, the step S2 is returned again;
for example, in a specific embodiment, the preset comparison value is 10, the absolute value of the difference value of the number of bytes is compared with the value 10, and when the difference value of the number of bytes is greater than 10, it is determined that the current scene changes; when the difference between the two bytes is less than or equal to 10, it is determined that the current scene is changed, and then the process returns to step S2 again.
It will be understood by those skilled in the art that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
The above description is only a preferred embodiment of the present invention, and it should be noted that, for those skilled in the art, several modifications and variations can be made without departing from the technical principle of the present invention, and these modifications and variations should also be regarded as the protection scope of the present invention.
Claims (4)
1. An image recognition method, comprising: the method comprises the following steps:
s1: acquiring an initial state of an image, marking the initial state as an image model, and marking the number of bytes of pixels of the image model as a model parameter;
s2: acquiring the image again, and comparing the number of bytes of the pixel of the image acquired again with the model parameter;
s3: when the difference value between the obtained pixel byte number and the model parameter is larger than a certain value, judging that the current scene changes; and when the difference value between the obtained pixel byte number and the model parameter is less than or equal to a certain value, judging that the current scene is not changed.
2. The image recognition method of claim 1, wherein: a comparison value is preset, and in step S3, the difference value between the number of bytes of the pixel and the model parameter is compared with the comparison value.
3. The image recognition method of claim 1, wherein: in step S3, after the comparison between the obtained number of bytes of pixels and the model parameter is completed, the process returns to step S2.
4. The image recognition method of claim 1, wherein: in step S1, the image initial state can be manually updated.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110725394.7A CN113343911A (en) | 2021-06-29 | 2021-06-29 | Image identification method |
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| Application Number | Priority Date | Filing Date | Title |
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| CN202110725394.7A CN113343911A (en) | 2021-06-29 | 2021-06-29 | Image identification method |
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| CN113343911A true CN113343911A (en) | 2021-09-03 |
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| CN202110725394.7A Pending CN113343911A (en) | 2021-06-29 | 2021-06-29 | Image identification method |
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Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20050237951A1 (en) * | 2004-04-21 | 2005-10-27 | Yang En-Hui | Method, system and software product for color image encoding |
| CN106878703A (en) * | 2017-03-14 | 2017-06-20 | 珠海全志科技股份有限公司 | A kind of drive recorder video recording detection method |
| CN110766243A (en) * | 2019-12-30 | 2020-02-07 | 恒大智慧科技有限公司 | Scenic spot toilet recommendation method, device and system |
| CN112954318A (en) * | 2021-01-19 | 2021-06-11 | 西安万像电子科技有限公司 | Data coding method and device |
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2021
- 2021-06-29 CN CN202110725394.7A patent/CN113343911A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20050237951A1 (en) * | 2004-04-21 | 2005-10-27 | Yang En-Hui | Method, system and software product for color image encoding |
| CN106878703A (en) * | 2017-03-14 | 2017-06-20 | 珠海全志科技股份有限公司 | A kind of drive recorder video recording detection method |
| CN110766243A (en) * | 2019-12-30 | 2020-02-07 | 恒大智慧科技有限公司 | Scenic spot toilet recommendation method, device and system |
| CN112954318A (en) * | 2021-01-19 | 2021-06-11 | 西安万像电子科技有限公司 | Data coding method and device |
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Application publication date: 20210903 |