A similar feature point matching method for aerial electric power tower images based on a one-ring neighborhood of vertices
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. T...
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| Format: | Article |
| Language: | English |
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EDP Sciences
2025-01-01
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| Series: | Science and Technology for Energy Transition |
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| Online Access: | https://www.stet-review.org/articles/stet/full_html/2025/01/stet20240303/stet20240303.html |
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| _version_ | 1841554616287756288 |
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| author | Chen Keyu Guo Jufu Wang Weijun Lei Bo Huang Hui Luo Lijing |
| author_facet | Chen Keyu Guo Jufu Wang Weijun Lei Bo Huang Hui Luo Lijing |
| author_sort | Chen Keyu |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-28fa24876912469cab43ad7dac71d443 |
| institution | Kabale University |
| issn | 2804-7699 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | EDP Sciences |
| record_format | Article |
| series | Science and Technology for Energy Transition |
| spelling | doaj-art-28fa24876912469cab43ad7dac71d4432025-01-08T11:23:51ZengEDP SciencesScience and Technology for Energy Transition2804-76992025-01-0180310.2516/stet/2024099stet20240303A similar feature point matching method for aerial electric power tower images based on a one-ring neighborhood of verticesChen Keyu0Guo Jufu1Wang Weijun2Lei Bo3Huang Hui4Luo Lijing5Guizhou Power Grid Co., Ltd. Guiyang Power Supply BureauGuizhou Power Grid Co., Ltd. Guiyang Power Supply BureauGuizhou Power Grid Co., Ltd. Guiyang Power Supply BureauGuizhou Power Grid Co., Ltd. Guiyang Power Supply BureauGuizhou Power Grid Co., Ltd. Guiyang Power Supply BureauGuizhou Power Grid Co., Ltd. Guiyang Power Supply BureauDue 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.https://www.stet-review.org/articles/stet/full_html/2025/01/stet20240303/stet20240303.htmlelectric power toweraerial imagesvertex one-ring neighborhoodsimilar feature point matchinglaplace pyramidfiltersbabbitt coefficients |
| spellingShingle | Chen Keyu Guo Jufu Wang Weijun Lei Bo Huang Hui Luo Lijing A similar feature point matching method for aerial electric power tower images based on a one-ring neighborhood of vertices Science and Technology for Energy Transition electric power tower aerial images vertex one-ring neighborhood similar feature point matching laplace pyramid filters babbitt coefficients |
| title | A similar feature point matching method for aerial electric power tower images based on a one-ring neighborhood of vertices |
| title_full | A similar feature point matching method for aerial electric power tower images based on a one-ring neighborhood of vertices |
| title_fullStr | A similar feature point matching method for aerial electric power tower images based on a one-ring neighborhood of vertices |
| title_full_unstemmed | A similar feature point matching method for aerial electric power tower images based on a one-ring neighborhood of vertices |
| title_short | A similar feature point matching method for aerial electric power tower images based on a one-ring neighborhood of vertices |
| title_sort | similar feature point matching method for aerial electric power tower images based on a one ring neighborhood of vertices |
| topic | electric power tower aerial images vertex one-ring neighborhood similar feature point matching laplace pyramid filters babbitt coefficients |
| url | https://www.stet-review.org/articles/stet/full_html/2025/01/stet20240303/stet20240303.html |
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