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OpenCV-based image blurring rapid detection method and tool

A technology for detection methods and detection tools, which can be used in image enhancement, image analysis, image data processing, etc., and can solve problems such as difficulties

Pending Publication Date: 2022-01-04
INSPUR TIANYUAN COMM INFORMATION SYST CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, it is rather difficult to define what is a low number of high frequencies or what is a high number of high frequencies

Method used

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  • OpenCV-based image blurring rapid detection method and tool
  • OpenCV-based image blurring rapid detection method and tool

Examples

Experimental program
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Effect test

Embodiment 1

[0051] combined with figure 1 , a fast detection method for image blurring based on OpenCV, the detection process is based on OpenCV technology, including:

[0052] Step S1, collecting user's avatar data, and the collected avatar data supports base64 character stream format or imagebuffer format.

[0053] Step S2 , performing format conversion on the collected avatar data to generate a matrix-based data grid Mat.

[0054] Step S3, converting the format-converted avatar data into a grayscale image, and performing noise reduction processing on the grayscale image.

[0055] Step S4, using the Laplacian operator to calculate the corresponding value of the denoised grayscale image.

[0056] Step S5 , setting a threshold, and comparing the threshold with the aforementioned corresponding value to determine whether the collected avatar data satisfies the definition.

[0057] Specific operations for setting thresholds:

[0058] Step S5.1, collecting avatar data of different users; ...

Embodiment 2

[0066] combined with figure 2 , the present embodiment proposes a kind of image fuzzy rapid detection tool based on OpenCV, and it is based on OpenCV, and realization module comprises: acquisition module 1, format conversion module 2, gray scale processing module 3, noise reduction module 4, calculation module 5, comparison judgment Module 6, set module 7.

[0067] The collection module 1 is used to collect user's avatar data, and the collected avatar data supports base64 character stream format or image buffer format.

[0068] The format conversion module 2 is used to perform format conversion on the collected avatar data to generate a matrix-based data grid Mat.

[0069] The grayscale processing module 3 is used to convert the format-converted avatar data into a grayscale image.

[0070] The denoising module 4 is used to perform denoising processing on the grayscale image, and then input the denoised grayscale image into the calculation module 5 .

[0071] The calculatio...

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Abstract

The invention discloses an OpenCV-based image blurring rapid detection method, which relates to the technical field of image detection, is based on an OpenCV technology, and comprises the following steps: collecting head portrait data of a user; performing format conversion on the acquired head portrait data to generate a matrix-based data grid Mat; converting the head portrait data after format conversion into a grayscale image; calculating a corresponding value of the grayscale image by using a Laplacian operator; and setting a threshold value, and comparing the threshold value with the corresponding value to judge whether the acquired head portrait data meets the definition or not. The invention also discloses an OpenCV-based image blurring rapid detection tool, which combines an acquisition module, a format conversion module, a gray processing module, a noise reduction module, a calculation module, a setting module and a comparison and judgment module with the above detection method, realizes detection of head portrait data, and prevents definition from being influenced by head portrait data blurring.

Description

technical field [0001] The invention relates to the technical field of image detection, in particular to an OpenCV-based rapid detection method and tool for image blur. Background technique [0002] At present, image detection is very important in some special application scenarios. For example, visual tasks such as face recognition or liveness detection that rely on microscopic details and textures are very sensitive to images. The first method to consider is to calculate the fast Fu Lie transform, and then check the distribution of low and high frequencies: if the image has only a few high frequencies, then the image is considered blurry. However, it is rather difficult to define what is a low number of high frequencies or what is a high number of high frequencies. [0003] OpenCV (Open Source Computer Vision) has been widely used in various image and video related projects, and has played an important role in the development of artificial intelligence and neural networks...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T5/00
CPCG06T2207/30201G06T5/73G06T5/70
Inventor 黄先林
Owner INSPUR TIANYUAN COMM INFORMATION SYST CO LTD
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