Title :
Orientation and damage inspection of insulators based on Tchebichef moment invariants
Author :
Liu, Guohai ; Zhu, Zhu ; Jie, Xu
Author_Institution :
Sch. of Electr. & Inf. Eng., Jiangsu Univ., Zhejiang
Abstract :
Based on the Tchebichef moment invariants, methods of orientation and damage inspection of insulators which was applied in the vision system of inspection robot on the power transmission lines was proposed in the paper. The image of insulators was first subjected to a normalization process to obtain rotation, scale and translation invariance. As feature vector, the Zernike moment invariants were then extracted from the normalized images. The recognition was realized by nearest neighbor feature matching. At last, damage of insulators was inspected by the gray level change rate of longitudinal tangent. Compared with Zernike moments and Hu moments, the accuracy of Tchebichef moment invariants performed much better.
Keywords :
Zernike polynomials; inspection; insulators; power transmission lines; Hu moments; Tchebichef moment invariants; Zernike moment invariants; damage inspection; image recognition; inspection robot; insulators; nearest neighbor feature matching; power transmission lines; vision system; Dielectrics and electrical insulation; Feature extraction; Inspection; Machine vision; Nearest neighbor searches; Neural networks; Poles and towers; Polynomials; Power transmission lines; Robot vision systems; Inspection robot; Orientation of insulators; Tchebichef moment invariants;
Conference_Titel :
Neural Networks and Signal Processing, 2008 International Conference on
Conference_Location :
Nanjing
Print_ISBN :
978-1-4244-2310-1
Electronic_ISBN :
978-1-4244-2311-8
DOI :
10.1109/ICNNSP.2008.4590307