Insulator recognition based on moments invariant features and Cascade AdaBoost classifier | |
He SY(何思远); Wang L(王玲); Xia Y(夏泳); Tang YD(唐延东)![]() | |
2013 | |
会议名称 | 2013 2nd International Conference on Mechatronics and Control Engineering, ICMCE 2013 |
会议日期 | August 28-29, 2013 |
会议地点 | Dalian, China |
关键词 | Classification (of information) Median filters Principal component analysis |
页码 | 362-367 |
中文摘要 | A method based on moments invariant features and cascade AdaBoost classifier for insulator recognition is put forward to solve the problem of poor performance of insulator recognition. At first, the insulator image is preprocessed by median filtering, dilating, eroding and Otsu thresholding. Then, for the better extraction of moments invariant features, the preprocessed insulator image is tilted correctly based on PCA (Principal Component Analysis). Next, the moments invariant features are extracted and chosen to compose complex classifier in the process of training AdaBoost. Finally, the complex AdaBoost classifiers are combined in a cascade method for insulator recognition. The results of experiments demonstrate that the proposed method can recognize the insulator from complex background in the mountainous area, and it has better robustness, accuracy and validity. © (2013) Trans Tech Publications, Switzerland. |
收录类别 | EI ; CPCI(ISTP) |
产权排序 | 1 |
会议主办者 | Queensland University of Technology; Korea Maritime University; Hong Kong Industrial Technology Research Centre; Inha University |
会议录 | Applied Mechanics and Materials
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会议录出版者 | Trans Tech Publications Ltd, |
会议录出版地 | Zurich-Durnten, Switzerland |
语种 | 英语 |
ISSN号 | 1660-9336 |
ISBN号 | 978-3-03785-894-3 |
WOS记录号 | WOS:000335121000071 |
内容类型 | 会议论文 |
源URL | [http://ir.sia.cn/handle/173321/13918] ![]() |
专题 | 沈阳自动化研究所_机器人学研究室 |
推荐引用方式 GB/T 7714 | He SY,Wang L,Xia Y,et al. Insulator recognition based on moments invariant features and Cascade AdaBoost classifier[C]. 见:2013 2nd International Conference on Mechatronics and Control Engineering, ICMCE 2013. Dalian, China. August 28-29, 2013. |
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