Article

Image recognition for on-line vibration monitoring system of transmission line

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Abstract

Image-based on-line monitoring system is widely applied in China recently, of which the image recognition is one of the key techniques. Considering the image feature and contour characteristic of the transmission line and such accessories as the damper, insulator chains, a recognition method based on chain code tracking and corner point detection is proposed. First extract the edge contour of the components after the image preprocessing, including graying, linear grey transforming upon the original image. Then trace chain code and detect corner points of the edge contour. Finally extract circle contour and determine its center point for the damper end face. Recognition experiment performed on fifty images proves that the proposed method is effective for detecting almost all corner points on image contour and recognizing the objects with 99% reliability.

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... In early work, the use of image processing algorithms to improve the visual perception of vibration dampers in images was the most common method. Usually, researchers use an appropriate feature extraction operator to detect vibration dampers [11]. In addition, there are studies that combine machine learning algorithms to improve the level of automation [1], and such methods were also the main direction of early research. ...
... Huang et al. [17] used grayscale processing, edge detection, threshold segmentation, morphological processing, and other technologies to calculate the rusted area ratio of the vibration damper to determine the degree of corrosion of the vibration damper and carried out displacement detection. Pan et al. [11] used the edge extraction operator to estimate the damage degree of the vibration damper. Extracting the edge of the vibration damper is also an effective detection method. ...
... The Inception Score (IS) is a common standard used to evaluate the quality of the output of the generative model, and the higher the value, the higher the clarity of the image. Its calculation formula is shown in Equation (11). ...
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