Numéro |
Sci. Tech. Energ. Transition
Volume 80, 2025
Emerging Advances in Hybrid Renewable Energy Systems and Integration
|
|
---|---|---|
Numéro d'article | 3 | |
Nombre de pages | 14 | |
DOI | https://doi.org/10.2516/stet/2024099 | |
Publié en ligne | 17 décembre 2024 |
Regular Article
A similar feature point matching method for aerial electric power tower images based on a one-ring neighborhood of vertices
Guizhou Power Grid Co., Ltd. Guiyang Power Supply Bureau, Guiyang 550000, Guizhou, China
* Corresponding author: ckycsg@126.com
Received:
29
August
2024
Accepted:
13
November
2024
Due to the susceptibility of images to various factors such as scale changes, imaging conditions, and image noise, traditional feature point matching methods are difficult to achieve ideal matching accuracy, leading to many challenges in the automatic analysis and processing of power tower images. To improve the matching accuracy of similar feature points in aerial images of electric power tower, this study proposes a method for matching similar feature points in aerial images of electric power tower based on a vertex ring neighborhood, addressing the problem of large matching errors caused by factors such as scale and imaging conditions. This method first adopts the feature point extraction technique of electric power tower image based on decomposition and filtering, and constructs the Laplacian pyramid of the original image. Subsequently, filter banks are used to decompose the pyramid image in different directions, extract local extremum points as candidate feature point sets, and merge them to obtain the final feature point set. On this basis, taking into account the spatial relationships and geometric characteristics around the feature points, a texture mapping algorithm based on vertex ring neighborhood and patch classification is applied to construct a vertex ring neighborhood structure and extract geometrically representative electric power tower features. Finally, by using a texture feature point matching method based on the principle of similarity, the similarity between the real-time image and the reference image features is calculated for matching, and combined with the Babbitt coefficient to remove mismatched feature points, accurate matching of similar feature points in aerial electric power tower images is achieved. The experimental results show that this method has a mean square error of less than 0.1 Pixel in matching similar texture feature points of aerial power tower images under various working conditions, significantly improving the matching accuracy and providing an effective tool for automatic analysis and processing of power tower images.
Key words: Electric power tower / Aerial images / Vertex one-ring neighborhood / Similar feature point matching / Laplace pyramid / Filters / Babbitt coefficients
© The Author(s), published by EDP Sciences, 2024
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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