Back to Search
Start Over
Recognition of Power Equipment Based on Multitask Sparse Representation
- Source :
- Scientific Programming, Vol 2021 (2021)
- Publication Year :
- 2021
- Publisher :
- Hindawi Limited, 2021.
-
Abstract
- Image analysis of power equipment has important practical significance for power-line inspection and maintenance. This paper proposes an image recognition method for power equipment based on multitask sparse representation. In the feature extraction stage, based on the two-dimensional (2D) random projection algorithm, multiple projection matrices are constructed to obtain the multilevel features of the image. In the classification process, considering that the image acquisition process will inevitably be affected by factors such as light conditions and noise interference, the proposed method uses the multitask compressive sensing algorithm (MtCS) to jointly represent multiple feature vectors to improve the accuracy and robustness of reconstruction. In the experiment, the images of three types of typical power equipment of insulators, transformers, and circuit breakers are classified. The correct recognition rate of the proposed method reaches 94.32%. In addition, the proposed method can maintain strong robustness under the conditions of noise interference and partial occlusion, which further verifies its effectiveness.
- Subjects :
- Article Subject
Computer science
business.industry
Random projection
Feature vector
Feature extraction
Pattern recognition
Sparse approximation
Computer Science Applications
QA76.75-76.765
Compressed sensing
Robustness (computer science)
Computer software
Noise (video)
Artificial intelligence
Projection (set theory)
business
Software
Subjects
Details
- ISSN :
- 1875919X and 10589244
- Volume :
- 2021
- Database :
- OpenAIRE
- Journal :
- Scientific Programming
- Accession number :
- edsair.doi.dedup.....f0da70136e18689b2a00e0a68a402979
- Full Text :
- https://doi.org/10.1155/2021/8322361