Weeds detection in UAV imagery using SLIC and the Hough transform

被引:0
|
作者
Bah, M. Dian [1 ]
Hafiane, Adel [2 ]
Canals, Raphael [1 ]
机构
[1] Univ Orleans, PRISME EA 4229, F-45072 Orleans, France
[2] INSA Ctr Val de Loire, PRISME EA 4229, F-45072 Orleans, France
来源
PROCEEDINGS OF THE 2017 SEVENTH INTERNATIONAL CONFERENCE ON IMAGE PROCESSING THEORY, TOOLS AND APPLICATIONS (IPTA 2017) | 2017年
关键词
Weeds detection; UAV; line detection; crop lines detection; Hough transform; SLIC; precision agriculture; CROP/WEED DISCRIMINATION; AGRONOMIC IMAGES; SEGMENTATION; ALGORITHM; CROP;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Traditional weeds controlling tended to be spraying herbicides in all the fields. Such method not only requires huge quantities of herbicides but impact environment and humans health. In this paper, we propose a new method of crop/weeds discrimination using imagery provided by an unmanned aerial vehicle (UAV). This method is based on the vegetation skeleton, the Hough transform and the spatial relationship of superpixels created by the simple linear iterative clustering (SLIC). The combination of the spatial relationship of superpixels and their positions in the detected crop lines allows to detect intraline weeds. Our method shows its robustness in presence of weed patches close to crop lines as well as for the detection of crop lines as for weed detection.
引用
收藏
页数:6
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