Extraction and recognition of insulator based on aerial image

Author

Tong, Wei-guo ; Li, Bao-shu ; Pei, Yu-long

Author_Institution

Dept. of Autom., North China Electr. Power Univ., Baoding, China

fYear

2011

fDate

15-17 April 2011

Firstpage

4195

Lastpage

4198

Abstract

This paper describes a method for extraction and recognition of insulator based on aerial image. After image preprocessing involve removing noise, enhancing the contrast, edge detection and image binarization, the model for the ramp edge given by Petrou is used to realize the image orientation and image segmentation. Based on the features are extracted from moment invariants and the shape and wavelet transform, a RBF neural network is used for recognition of the insulator from the background, and some damages of insulator are detected in the meanwhile. The experimental results show clearly that this method is feasible and effective.

Keywords

edge detection; feature extraction; image segmentation; insulators; radial basis function networks; RBF neural network; aerial image; edge detection; feature extraction; image binarization; image orientation; image preprocessing; image segmentation; insulator extraction; insulator recognition; ramp edge; wavelet transform; Feature extraction; Image edge detection; Image segmentation; Insulators; Wavelet transforms; RBF neural network; feature extraction; image processing; insulator; wavelet transform;

fLanguage

English

Publisher

ieee

Conference_Titel

Electric Information and Control Engineering (ICEICE), 2011 International Conference on

Conference_Location

Wuhan

Print_ISBN

978-1-4244-8036-4

Type

conf

DOI

10.1109/ICEICE.2011.5778174

Filename

5778174