Detection of power line insulators on digital images with the use of laser spots. Issue 12 (13th September 2019)

• Record Type: Journal Article
• Authors: Tomaszewski, Michał; Michalski, Paweł; Ruszczak, Bogdan; Zator, Sławomir
• Is Part Of: IET image processing. Volume 13:Issue 12(2019)
• Page Start: 2358
• Page End: 2366
• Publication Date: 2019-09-13
• Subjects: image classification -- image registration -- power cables -- insulators -- power engineering computing -- video signal processing -- object detection; registered video data -- pixel intensity profiles -- image profile -- high‐voltage power line insulators -- digital image processing -- laser spots -- digital signal testing -- spot detection -- pattern classification -- open‐access dataset -- power line insulator detection; Image processing -- Periodicals; 621.36705
• DOI: 10.1049/iet-ipr.2018.6284
• Languages: English
• ISSNs: 1751-9659

Abstract

Abstract : The massive growth of technologies used to register and process digital images allow for their application in evaluating the technical condition of power lines. However, it is not possible without a set of dedicated methods for obtaining diagnostic information based on registered video data. The method described here details the detection of power line insulators in digital images featuring diversified backgrounds using laser spots. The algorithm of detecting an insulator in analysed images is based on testing the digital signal of pixel intensity profiles read between subsequent pairs of laser points in the image. The method is comprised of the following stages: import the image with laser spots, detection of spots on the image, and pattern classification of each image profile that is calculated for each found laser spots pair. The evaluated profiles depicting an insulator were characterised by regular patterns that reflect the target structure. To classify profiles as either insulator containing or non‐containing, several steps should be followed: averaging the signal, removing the linear trend, finding and alternating the minima and maxima. The performance of the proposed method was verified using an open‐access dataset, comprised of various scenes featuring high‐voltage power line insulators.