Preprocessing method based on inspection image

Abstract

The invention discloses a preprocessing method based on an inspection image, and the method comprises: an image defogging algorithm which removes the impact on the image quality from a weather factor,and guarantees the original features of an image; an image segmentation algorithm which is used to obtain a condition area satisfying uniformity and connectivity, and extract an interested target ora meaningful area; an image denoising algorithm for removing a large amount of noise introduced in the imaging process and ensuring the original characteristics of the target object; an image enhancement algorithm, in whch image enhancement processing is used for optimizing the image quality, emphasizing the region of interest in the image and improving the readability of the image; and an image restoration algorithm which is used for processing the image which is degraded due to distortion, blurring, distortion or noise mixing to obtain a source image which is restored as much as possible. The technical scheme of the embodiment of the invention is used for preprocessing the inspection image, improving the quality of the inspection image, highlighting the characteristics of the target object, facilitating the later intelligent recognition and classification, and greatly reducing the cost compared with a mode of processing only depending on manual discrimination.

Description

technical field [0001] The invention belongs to the technical field of line maintenance, in particular relates to the maintenance of power transmission lines, in particular to a preprocessing method based on inspection images. Background technique [0002] With the development of computer technology and image processing technology, new inspection methods based on online monitoring, robots, and drones continue to emerge. If the digital images acquired by video cameras and cameras are only processed by manual screening, it will consume a lot of manpower. At the same time, because of the collection angle, weather conditions, transmission factors and other reasons, the collected images are not ideal. The factors that seriously affect the quality of the collected images mainly include the following aspects: [0003] The influence of lighting and complex scenes. Even if the image is taken at the same location, at different times, such as noon and dusk, sunny and rainy days, etc...

AI Technical Summary

Problems solved by technology

[0007] To sum up, the transmission line inspection image has the characteristics of complex dynamic background, target rotation, stretching, occlusion, complexity and randomness of relative motion of the target, which makes the target not prominent enough in the image and difficult to process.

At the same time, the edges of the pictures collected in the field are blurred, the contrast is relatively poor, and there are randomly distributed points and small block noises in the spatial domain, which leads to unsatisfactory post-processing results.

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