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A hybrid approach for efficient detection of plastic mulching films in cotton

文献类型: 外文期刊

作者: Fang, Jingjing 1 ; Jiang, Yu 1 ; Yue, Jun 1 ; Wang, Zhicheng 3 ; Li, Daoliang 1 ; Li, Zhenbo 1 ;

作者机构: 1.China Agr Univ, Coll Informat & Elect Engn, Beijing 100083, Peoples R China

2.Ludong Univ, Coll Informat & Elect Engn, Yantai, Peoples R China

3.Shandong Acad Agr Sci, Jinan, Peoples R China

关键词: Cotton;Foreign fibers;Plastic mulching film;Objectness measurement;Otsu

期刊名称:MATHEMATICAL AND COMPUTER MODELLING ( 影响因子:1.366; 五年影响因子:1.602 )

ISSN:

年卷期:

页码:

收录情况: SCI

摘要: Plastic mulching films (PMFs) in cotton seriously affect the quality of cotton products, especially for spinning and dyeing. However, PMFs still cannot be detected accurately and efficiently. This paper focuses on automatic PMF detection from images captured by a foreign-fiber detection machine. A novel method for PMF detection is proposed. First, object identification is used to detect significant regions. Then an inspection algorithm is used to calculate the weight for each significant region and the highest one is selected as the mulching detection result. Experiments demonstrate that our method can accurately detect and count PMFs in cotton. Compared to existing Otsu adaptive threshold segmentation and object detection methods, our hybrid method shows improvements in film detection of approximately 36% and 10%, respectively.

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