ICDIP_2022_paper_157.pdf (1.41 MB)
Identification and localisation of multiple weeds in grassland for removal operation
conference contribution
posted on 2023-06-10, 03:47 authored by Jinjin Wang, Xiaopeng Yaob, Bao Kha NguyenBao Kha NguyenWeeds are a common issue in agriculture. Image-based weed identification has regained popularity in recent years as computing power increases. Researchers have successfully applied weed detection in the crop field and have combined the sensor (e.g.camera) and mechanical such as robotic weeders to get the location of the weeds. Meanwhile, many studies also have been conducted on the two classifications between grass and weed. However, there is no excellent and comprehensive weed dataset in reality because weeds are always similar and difficult to obtain by non-specialists. Moreover, it is challenging to identify weeds from grasslands for their similar colors, sizes, and shapes. We investigate three weeds (Bitter Gentian, Hawk's Beard, Pedunculate) relatively common in grasslands. Then, we select the typical grassland dominated by the above weeds for data collection. A natural and effective dataset is built and has generality in the scene of actual grassland. Secondly, we extract image features, including Color, Histogram, and orientation gradient histogram (HOG), and make various combinations to accurately and comprehensively reflect the actual characteristics of weeds. Thirdly, we propose a "core zone" algorithm to locate the weeds. The algorithm mainly adopts technology in image processing, such as threshold segmentation and morphological transformations. Experiments show that our binary classifier is more accurate than the comparison method, and the accuracy of the multi-classifier is also high. In addition, the algorithm for weeds location is more efficient than the comparative method.
History
Publication status
- Published
File Version
- Accepted version
Journal
SPIE Conference ProceedingsPublisher
SPIE Digital LibraryExternal DOI
Volume
12342Page range
1-10Event name
The 14th International Conference on Digital Image Processing (ICDIP 2022)Event location
Wuhan, ChinaEvent type
conferenceEvent date
20th - 23rd May 2022ISBN
9781510646001Department affiliated with
- Engineering and Design Publications
Full text available
- Yes
Peer reviewed?
- Yes
Legacy Posted Date
2022-06-06First Open Access (FOA) Date
2022-07-21First Compliant Deposit (FCD) Date
2022-07-21Usage metrics
Categories
No categories selectedLicence
Exports
RefWorks
BibTeX
Ref. manager
Endnote
DataCite
NLM
DC