Electric Equipment Image Recognition Based on Sparse Representation for the Safety of Power Distribution. (August 2019)

• Record Type: Journal Article
• Authors: Ni, Changsong; Lin, Xuesong; Liu, Guicai; Liu, Shijun
• Is Part Of: IOP conference series. Volume 592(2019)
• Publication Date: 2019-08
• Subjects: Materials science -- Periodicals; 620.1105
• DOI: 10.1088/1757-899X/592/1/012157
• Languages: English
• ISSNs: 1757-8981

Abstract

Abstract: Electric equipment image analysis has important meanings to power line inspection and repairment. This paper proposes an electric equipment image recognition method based on sparse representation. Considering the image collection is inevitably influenced by the light condition and noise corruption, this paper uses Bayesian compressive sensing algorithm to solve the sparse representation problem. The algorithm has good robustness to noises and interferences, which is suitable to handle the conditions in electrical equipment images. In the experiments, three electrical equipments, i.e., insulators, power transformers, and breakers, are classified and the accuracy reaches 93.56%. In addition, the robustness of the proposed method under noise corruption is also superior. All the results validate the effectiveness of the proposed method.