Feature Fusion Based Insulator Detection for Aerial Inspection
文献类型：会议论文
| 作者 | YAN Tiantian1,2 ; YANG Guodong2; YU Junzhi2
|
| 出版日期 | 2017 |
| 会议日期 | 2017-7 |
| 会议地点 | Dalian, China |
| 关键词 | Insulator Location Feature-fusion Power Line Inspection Hog Lbp |
| 英文摘要 | ; This paper presents a detection method of insulator stings for aerial inspection based on feature-fusion. The local subimages of insulator strings are firstly collected from aerial videos and tagged to establish a training dataset. The fusion feature is then composed by the histogram of oriented gradients (HOG) feature and local binary pattern (LBP) feature after the principal component analysis (PCA) dimension reduction separately. A training model is developed by SVM algorithm with the fusion feature. At the detection phase, threshold segmentation and morphological operation are adopted to preprocess the images. The sliding window method is then used to search the candidate region and the non-maximum suppression (NMS) method is adopted to fuse the candidate windows. Finally, the position of the insulator strings can be calculated by linear fitting. Both the efficiency and the effectiveness of the proposed method are verified through experiments on locating the multi-angle insulator strings under complex backgrounds. |
| 源URL | [http://ir.ia.ac.cn/handle/173211/20921]  |
| 专题 | 自动化研究所_复杂系统管理与控制国家重点实验室_先进机器人控制团队 |
| 作者单位 | 1.University of Chinese Academy of Sciences 2.State Key Laboratory of Management and Control for Complex Systems, Institute of Automation of, Chinese Academy of Sciences |
| 推荐引用方式 GB/T 7714 | YAN Tiantian,YANG Guodong,YU Junzhi. Feature Fusion Based Insulator Detection for Aerial Inspection[C]. 见:. Dalian, China. 2017-7. |
入库方式： OAI收割
来源：自动化研究所
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