Image quality judgment algorithm based on local texture features

A texture feature and image quality technology, applied in image analysis, image enhancement, image data processing and other directions, can solve the problems of poor image blur detection effect, poor algorithm robustness, single application scenario, etc., to improve performance and high accuracy , the effect of fast detection

Active Publication Date: 2021-07-09
第六镜科技(成都)有限公司
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Problems solved by technology

In the face recognition task, if these blurred face images are not restricted, it will affect the pass rate of face recognition and the user experience
Through searching and investigating the existing methods of judging blurred images, it is found that the existing methods can only detect and filter some blurred images, and the robustness of the algorithm is poor, and the application scenarios are relatively single. Most of the algorithms can only detect motion The blur detection is good, but the image blur detection effect caused by light, camera hardware imaging, etc. is poor

Method used

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  • Image quality judgment algorithm based on local texture features

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Embodiment Construction

[0016] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0017] see figure 1 , this embodiment provides a technical solution:

[0018] A kind of image quality judgment algorithm based on local texture feature comprises the following steps:

[0019] Step 1: Input the image to be detected and scale it to the specified size;

[0020] Step 2: converting the scaled image from RGB color space to grayscale space;

[0021] Step 3: Select a 3x3 sliding window in the image, and the sliding window starts from ...

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Abstract

The invention discloses an image quality judgment algorithm based on local texture features. The image quality judgment algorithm comprises the following steps: inputting a to-be-detected image and zooming the to-be-detected image to a specified size; converting the zoomed image from an RGB color space to a gray scale space; selecting a 3 * 3 sliding window from the image, wherein the sliding window slides rightwards from the upper left corner of the image with the step length being 1; in each time of sliding, multiplying the pixel values in the sliding window and a fixed 3 * 3 matrix element by element, and adding the final results in another matrix A, storing the result, and finally calculating the variance of the matrix A, and setting a fuzzy detection threshold value t1 according to the variance. According to the provided image quality judgment algorithm based on the local texture features, the performance of image fuzzy detection is effectively improved through a cascaded fuzzy detection method, and compared with an existing edge fuzzy detection technology, the fuzzy detection method based on the image edges is higher in detection speed and higher in accuracy.

Description

technical field [0001] The invention relates to the related technical field of computer digital image processing, in particular to an image quality judgment algorithm based on local texture features. Background technique [0002] When the camera is shooting an object, it is inevitable to produce blurred images due to the high-speed movement of the object, light, and camera hardware imaging. In the face recognition task, if these blurred face images are not restricted, it will affect the pass rate of face recognition and the user experience. Through searching and investigating the existing methods of judging the blurred images, it is found that the existing methods can only detect and filter some blurred images, and the robustness of the algorithm is poor, the application scenarios are relatively single, and most algorithms can only detect and filter the blurred images. The blur detection is good, but the image blur detection effect caused by light, camera hardware imaging, ...

Claims

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Application Information

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IPC IPC(8): G06T7/00G06T7/41G06T7/90G06T5/00
CPCG06T7/0002G06T7/41G06T7/90G06T2207/10004G06T2207/30168G06T5/70
Inventor 刘有亮叶雨桐
Owner 第六镜科技(成都)有限公司
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