Detection method of power line under uneven lightness for flying-walking power line inspection robot

Bo Li Sr.; Xinyan Qin; Jin Lei; Yujie Zeng; Jie Zhang; Bo Jia; Huidong Li; Zhaojun Li

doi:10.1117/12.2611653

11 November 2021 Detection method of power line under uneven lightness for flying-walking power line inspection robot

Bo Li Sr., Xinyan Qin, Jin Lei, Yujie Zeng, Jie Zhang, Bo Jia, Huidong Li, Zhaojun Li

Proceedings Volume 12076, 2021 International Conference on Image, Video Processing, and Artificial Intelligence; 1207609 (2021) https://doi.org/10.1117/12.2611653
Event: Fourth International Conference on Image, Video Processing, and Artificial Intelligence (IVPAI 2021), 2021, Shanghai, China

Abstract

Due to the variation of sunlight conditions resulting in uneven lightness in images, the details of target objects tend to hide in the dark or bright regions, which is adverse to following image processing. To reliably land on the power line under the change of lightness, the flying-walking power line inspection robot (FPLIR) needs reliable detection for the power line. In this paper, a machine vision-based detection method of power line is proposed to adapt different lightness. Firstly, a visual system of the FPLIR is designed to collect and process power line images. Secondly, the multi-scale retinex (MSR) algorithm is used to reduce the influence of lightness. Then, the local binary pattern (LBP) map of power line image is generated by the LBP operator and is divided into many blocks. An LBP histogram vector is calculated for every block, then the first-order entropy and second-order entropy of every histogram vector are calculated. Finally, the first-order entropy, the second-order entropy, and the edge density of power line image are used as the feature vector of fuzzy c-means (FCM) to obtain the power line region. The experimental result shows that the accuracy of the proposed method is 82.6%, which is 9.3% more than the method without image enhancement. Thus, the proposed method can effectively detect power line, improving the robustness and accuracy of power line detection (PLD) during the FPLIR landing.

Citation Download Citation

Bo Li Sr., Xinyan Qin, Jin Lei, Yujie Zeng, Jie Zhang, Bo Jia, Huidong Li, and Zhaojun Li "Detection method of power line under uneven lightness for flying-walking power line inspection robot", Proc. SPIE 12076, 2021 International Conference on Image, Video Processing, and Artificial Intelligence, 1207609 (11 November 2021); https://doi.org/10.1117/12.2611653

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
7 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Image enhancement

Inspection

Cameras

Image segmentation

Binary data

Edge detection

Visualization

Show All Keywords

Keywords/Phrases

Search In:

Publication Years