Object Description Based on Local Features Repeatability

Tomaszewski, Michał; Michalski, Paweł; Osuchowski, Jakub

doi:10.1007/978-3-030-72254-8_28

Cited by 3 publications

(2 citation statements)

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“…The next step of the described method is determining specific points on the analysed digital image, which may be located both on the insulator and outside it. For this purpose, the method presented in the paper [ 20 ] was used, which consists of selecting characteristic local features in the images to detect specific objects of the power line in various scenes. The research described in the paper aimed to automate searching for characteristic objects in digital images with a limited training set.…”

Section: Methodsmentioning

confidence: 99%

“…In the study, the authors used the data set they collected (for the data set see the attached Supplementary Materials ), consisting of images obtained during an Unmanned Aerial Vehicle (UAV) flight along a high-voltage line. The starting point for the conducted analyses was the results of the research described in the publication [ 20 ], presenting the method of describing objects on digital images based on analysing the frequency of specific points. As a result of its application for the constructed data set, a set of points characteristic for insulators of transmission lines for each digital image was obtained.…”

Section: Introductionmentioning

confidence: 99%

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Detection of Power Line Insulators in Digital Images Based on the Transformed Colour Intensity Profiles

Tomaszewski

Gasz

Osuchowski

2023

Sensors

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Proper maintenance of the electricity infrastructure requires periodic condition inspections of power line insulators, which can be subjected to various damages such as burns or fractures. The article includes an introduction to the problem of insulator detection and a description of various currently used methods. Afterwards, the authors proposed a new method for the detection of the power line insulators in digital images by applying selected signal analysis and machine learning algorithms. The insulators detected in the images can be further assessed in depth. The data set used in the study consists of images acquired by an Unmanned Aerial Vehicle (UAV) during its overflight along a high-voltage line located on the outskirts of the city of Opole, Opolskie Voivodeship, Poland. In the digital images, the insulators were placed against different backgrounds, for example, sky, clouds, tree branches, elements of power infrastructure (wires, trusses), farmland, bushes, etc. The proposed method is based on colour intensity profile classification on digital images. Firstly, the set of points located on digital images of power line insulators is determined. Subsequently, those points are connected using lines that depict colour intensity profiles. These profiles were transformed using the Periodogram method or Welch method and then classified with Decision Tree, Random Forest or XGBoost algorithms. In the article, the authors described the computational experiments, the obtained results and possible directions for further research. In the best case, the proposed solution achieved satisfactory efficiency (F1 score = 0.99). Promising classification results indicate the possibility of the practical application of the presented method.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%