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Identification and location of catenary insulator in complex background based on machine vision

Xiaotong Yao, Yingli Pan, Li Liu, Xiao Cheng

Year
2018
Citations
4
Access
Open access

Abstract

It is an important premise to locate insulator precisely for fault detection. Current location algorithms for insulator under catenary checking images are not accurate, a target recognition and localization method based on binocular vision combined with SURF features is proposed. First of all, because of the location of the insulator in complex environment, using SURF features to achieve the coarse positioning of target recognition; then Using binocular vision principle to calculate the 3D coordinates of the object which has been coarsely located, realization of target object recognition and fine location; Finally, Finally, the key is to preserve the 3D coordinate of the object’s center of mass, transfer to the inspection robot to control the detection position of the robot. Experimental results demonstrate that the proposed method has better recognition efficiency and accuracy, can successfully identify the target and has a define application value.

Keywords

Computer visionArtificial intelligenceCatenaryComputer scienceRobotCognitive neuroscience of visual object recognitionBinocular visionMachine visionInsulator (electricity)Object detection

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