Image Variation Parameter Recognition of Electrical Power Equipment Based on SIFT Feature Matching

doi:10.11930/j.issn.1004-9649.2012.11.60.4

Abstract

Abstract: In video monitoring system of substation, in-process video inspection is used to detect abnormalities in timely so as to avoid failures. Changes in certain parameters of the image constitute an important basis in identifying the changes in image status. A power installation image change parameter identification algorithm based on SIFT, OTSU and RANSAC feature matching was presented. Firstly, a SIFT feature matching was performed on the sample image and monitoring image. Then the interference matching feature points were eliminated in combination with OTSU, and the RANSAC random sampling agreement algorithm was used to eliminate the wrong matching feature point. Finally, two important parameters including the variation angle and zoom coefficient of power installation image were identified based on the matching result. As is proved in the simulation test, this algorithm features simplicity and high precision and it can be used in recognizing the electric power tower inclination angle and meterneedle rotation angle. Meanwhile it can be used in recognizing the zoom coefficient in video inspection as well.

Key words: electrical power equipment, SIFT feature match, sample image, equipment monitoring image, variation angle, zoom coefficient

CLC Number:

TP391.4

YU Ping, DONG Bao-guo. Image Variation Parameter Recognition of Electrical Power Equipment Based on SIFT Feature Matching[J]. Electric Power, 2012, 45(11): 60-64.

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URL: https://www.electricpower.com.cn/EN/10.11930/j.issn.1004-9649.2012.11.60.4

https://www.electricpower.com.cn/EN/Y2012/V45/I11/60

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