Abstract
With the development of the electricity industry in our country, the kinds and the quantities of electrical equipment are increasing quickly. When the electrical equipment is checked and evaluated, the recognition of equipment is very important. In this paper, based on gray level co-occurrence matrix to extract the texture of equipment, we proposed a way to identify the electrical equipment. First it uses the gray level co-occurrence matrix texture matching recognition of electrical equipment, and then adopts the method of fuzzy logic according to the result of the match on the classified recognition of electric equipment. By the experiments, the correctness and feasibility of identification method to the electrical equipment are proved.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Liu, H.-B., Hu, B., Wang, X.-Y.: Thinking about “much starker choices-and graver consequences-in” distribution network development. J. China Power 48(1), 21–24 (2015)
Zhao, J.-J., Liu, H.: Remote monitoring system in the application of the computer room management. J. Shijiazhuang Inst. 9(3), 89–93 (2007)
Yang, J.-H., Liu, J., Jian, Z., et al.: Combination of watershed and automatic seed region growing segmentation algorithm. Chin. J. Image Graph 15(1), 63–68 (2011)
Stricker, M., Orengo, M.: Similarity of color images. Storage Retr. Image Video Databases III 2420, 381–392 (1995)
Acknowledgements
This work is supported by the Science and Technology Research Project of State Grid Corporation of China (526816160024).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer International Publishing AG
About this paper
Cite this paper
Ou, Q. et al. (2018). Feature Extraction of Electrical Equipment Identification Based on Gray Level Co-occurrence Matrix. In: Qiao, F., Patnaik, S., Wang, J. (eds) Recent Developments in Mechatronics and Intelligent Robotics. ICMIR 2017. Advances in Intelligent Systems and Computing, vol 690. Springer, Cham. https://doi.org/10.1007/978-3-319-65978-7_30
Download citation
DOI: https://doi.org/10.1007/978-3-319-65978-7_30
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-65977-0
Online ISBN: 978-3-319-65978-7
eBook Packages: EngineeringEngineering (R0)