Name
Abstract | ||
|---|---|---|
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. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1016/j.mcm.2012.12.018 | Mathematical and Computer Modelling |
Keywords | Field | DocType |
Cotton,Foreign fibers,Plastic mulching film,Objectness measurement,Otsu | Object detection,Mathematical optimization,Pattern recognition,Spinning,Segmentation,Artificial intelligence,Dyeing,Mathematics | Journal |
Volume | Issue | ISSN |
58 | 3 | 0895-7177 |
Citations | PageRank | References |
1 | 0.38 | 4 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jingjing Fang | 1 | 25 | 5.81 |
| Yu Jiang | 2 | 9 | 3.06 |
| Jun Yue | 3 | 66 | 4.89 |
| Zhicheng Wang | 4 | 176 | 17.00 |
| Daoliang Li | 5 | 334 | 81.09 |
| Zhenbo Li | 6 | 69 | 6.96 |