An Intelligent Weed Recognition Method Based on Optical Patrol Image
Power inspection is currently carried out mainly by drones. The weeds around the power equipment may cause potential safety hazards when the patrol images acquired by drones are used for patrol inspection, it is therefore necessary to recognize the weeds in the image. In this paper, a method for int...
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| Format: | Article |
| Language: | zho |
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State Grid Energy Research Institute
2019-11-01
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| Series: | Zhongguo dianli |
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| Online Access: | https://www.electricpower.com.cn/CN/10.11930/j.issn.1004-9649.201902152 |
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| author | Guoliang YUE Yanqiao LU Hao CHANG Cuiying SUN |
| author_facet | Guoliang YUE Yanqiao LU Hao CHANG Cuiying SUN |
| author_sort | Guoliang YUE |
| collection | DOAJ |
| description | Power inspection is currently carried out mainly by drones. The weeds around the power equipment may cause potential safety hazards when the patrol images acquired by drones are used for patrol inspection, it is therefore necessary to recognize the weeds in the image. In this paper, a method for intelligent recognition of weeds is proposed for power patrol inspection based on optical patrol images. Based on the feature of weeds in the optical images, and combined with the convolutional neural network method, the problem of weed recognition near the power equipment in optical patrol images is solved. By amplifying and preprocessing the sample data of the optical patrol images, and introducing the region proposal network, the image features of the fixed number of candidate frames are extracted from the images. Then the network is connected to the improved image classification network to obtain a final convolutional neural network model. The experiments show that the accuracy rate can reach 97.98%, and the average time taken for detecting a 600×600 image is around 0.256 seconds, which meets the requirements of efficient recognition while ensuring accuracy. |
| format | Article |
| id | doaj-art-ff51e7a6cb3f4032bc6e72201955f0f1 |
| institution | OA Journals |
| issn | 1004-9649 |
| language | zho |
| publishDate | 2019-11-01 |
| publisher | State Grid Energy Research Institute |
| record_format | Article |
| series | Zhongguo dianli |
| spelling | doaj-art-ff51e7a6cb3f4032bc6e72201955f0f12025-08-20T02:06:23ZzhoState Grid Energy Research InstituteZhongguo dianli1004-96492019-11-01521113814410.11930/j.issn.1004-9649.201902152zgdl-52-11-yueguoliangAn Intelligent Weed Recognition Method Based on Optical Patrol ImageGuoliang YUE0Yanqiao LU1Hao CHANG2Cuiying SUN3State Grid Hebei Electric Power Co., Ltd., Shijiazhuang 050041, ChinaState Grid Hebei Electric Power Research Institute, Shijiazhuang 050021, ChinaMaintenance Branch of State Grid Hebei Electric Power Co., Ltd., Shijiazhuang 050070, ChinaState Grid Hebei Electric Power Research Institute, Shijiazhuang 050021, ChinaPower inspection is currently carried out mainly by drones. The weeds around the power equipment may cause potential safety hazards when the patrol images acquired by drones are used for patrol inspection, it is therefore necessary to recognize the weeds in the image. In this paper, a method for intelligent recognition of weeds is proposed for power patrol inspection based on optical patrol images. Based on the feature of weeds in the optical images, and combined with the convolutional neural network method, the problem of weed recognition near the power equipment in optical patrol images is solved. By amplifying and preprocessing the sample data of the optical patrol images, and introducing the region proposal network, the image features of the fixed number of candidate frames are extracted from the images. Then the network is connected to the improved image classification network to obtain a final convolutional neural network model. The experiments show that the accuracy rate can reach 97.98%, and the average time taken for detecting a 600×600 image is around 0.256 seconds, which meets the requirements of efficient recognition while ensuring accuracy.https://www.electricpower.com.cn/CN/10.11930/j.issn.1004-9649.201902152patrol imageconvolutional neural networkregion proposalimage classificationweed recognitionartificial intelligence and big data application |
| spellingShingle | Guoliang YUE Yanqiao LU Hao CHANG Cuiying SUN An Intelligent Weed Recognition Method Based on Optical Patrol Image Zhongguo dianli patrol image convolutional neural network region proposal image classification weed recognition artificial intelligence and big data application |
| title | An Intelligent Weed Recognition Method Based on Optical Patrol Image |
| title_full | An Intelligent Weed Recognition Method Based on Optical Patrol Image |
| title_fullStr | An Intelligent Weed Recognition Method Based on Optical Patrol Image |
| title_full_unstemmed | An Intelligent Weed Recognition Method Based on Optical Patrol Image |
| title_short | An Intelligent Weed Recognition Method Based on Optical Patrol Image |
| title_sort | intelligent weed recognition method based on optical patrol image |
| topic | patrol image convolutional neural network region proposal image classification weed recognition artificial intelligence and big data application |
| url | https://www.electricpower.com.cn/CN/10.11930/j.issn.1004-9649.201902152 |
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