Open AccessResearch on Rapeseed Counting Based on Machine Vision
Author(s) -
Shunzheng Peng,
Zhijuan Zhao,
Xiaobo Wu,
Yuanbin Yue,
Lijie Li,
Zhu Weng,
Chuen-Tsai Sun
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1757/1/012028
Subject(s) - rapeseed , kernel (algebra) , computer science , artificial intelligence , agricultural engineering , computer vision , mathematics , engineering , agronomy , biology , discrete mathematics
Thousand-kernel weight is an important agronomic parameter of rapeseed. In order to quickly realize the grain count, shorten the measurement cycle of the thousand-grain weight, in this paper, we propose a grain counting method based on image detection, by testing 300 rapeseed images, and the results showed that the detection rate reached 89.33%.