Transmission line aerial image data cleaning method based on content awareness

A technology for aerial imagery and power transmission lines, applied in the field of image processing, can solve problems such as lack of distortion, affect image quality, and local image distortion without too much consideration, and achieve accurate quantitative recognition accuracy, strong self-adaptive ability, and strong generalization ability Effect

Pending Publication Date: 2022-07-29
NORTHWESTERN POLYTECHNICAL UNIV
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Problems solved by technology

The problem is that the traditional algorithm needs to convert the image into a fixed-length feature vector, which will affect the quality of the image; in addition, the scalability is not very good, and different application scenarios require different algorithms
The CG-DIQA method proposed in 2018: Convert the input image to a grayscale image, scale it to a fixed size, and estimate the quality score of the document image after calculating the standard deviation. This method cannot predict the quality of occluded images.
The problem is that CNN requires that the input image size is fixed, some need to be cropped to a fixed shape, some need to be resized, and can

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  • Transmission line aerial image data cleaning method based on content awareness

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specific Embodiment

[0044] (1) By cooperating with the power department, the aerial image of the transmission line is obtained as the original data set DataSet 1 , preprocess the acquired aerial images; use the Vision Transfomer algorithm to build a self-recognition classifier for a single image, identify each image in the data set, and use the classifier to classify the recognized images; There are two categories including insulator parts and those that do not include insulator parts, and those that include insulator parts are marked as Class A, otherwise, they are classified as Class B images.

[0045] (i) Input an image i, and note that the probability of being recognized as class A is P iA , the probability of being identified as class B is P iB , the P iB Results in more than 90% of the images are put into the collection DataSet 2 , the sample dataset becomes a DataSet 1 -DataSet 2 , denoted as DataSet 3 .

[0046] (ii)P iB Although the result is above 90%, it may still contain image...

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Abstract

The invention discloses a content awareness-based power transmission line aerial image data cleaning method, which comprises the following steps of: firstly, constructing a self-classification model, and cleaning an image which does not contain an insulator part in an aerial image; training a model for extracting image content by using the residual data set; the method comprises the following steps: acquiring local and global features of an image, establishing a quality perception rule according to different influence degrees of local and global contents on image quality, mapping an image quality score function, and finally screening the image according to image quality scores. According to the invention, mass aerial image data can be effectively cleaned, so that clearer and higher-quality images can be obtained.

Description

technical field [0001] The invention belongs to the technical field of image processing, and in particular relates to a method for cleaning aerial image data of transmission lines. Background technique [0002] Electric power departments need to conduct regular power inspections, and drones have become a trend to replace manual inspections. The information extracted from aerial images is used to locate the faults of insulators of transmission line components. However, drones will collect a large number of invalid images, and some of the images will be distorted during the transmission process due to hardware equipment; too much invalid data, on the one hand, will lead to a surge in the amount of manual detection tools, reduced accuracy, and reduced timeliness; On the other hand, it is not conducive to building a better and more practical insulator defect detection model. Therefore, cleaning the massive aerial images of transmission lines and screening out high-quality image...

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Application Information

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IPC IPC(8): G06V10/764G06V10/40G06V10/20G06K9/62
CPCG06F18/24
Inventor 郭阳明范颜军
Owner NORTHWESTERN POLYTECHNICAL UNIV
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