Journal
SENSORS
Volume 22, Issue 4, Pages -Publisher
MDPI
DOI: 10.3390/s22041617
Keywords
vegetable size measurement; computer vision; stereo camera; keypoints detection
Ask authors/readers for more resources
This paper proposes an intelligent method for vegetable recognition and size estimation using computer vision and stereo cameras in agricultural automation. Experimental results show that the method can accurately classify and estimate the size of vegetables.
This work focuses on the problem of non-contact measurement for vegetables in agricultural automation. The application of computer vision in assisted agricultural production significantly improves work efficiency due to the rapid development of information technology and artificial intelligence. Based on object detection and stereo cameras, this paper proposes an intelligent method for vegetable recognition and size estimation. The method obtains colorful images and depth maps with a binocular stereo camera. Then detection networks classify four kinds of common vegetables (cucumber, eggplant, tomato and pepper) and locate six points for each object. Finally, the size of vegetables is calculated using the pixel position and depth of keypoints. Experimental results show that the proposed method can classify four kinds of common vegetables within 60 cm and accurately estimate their diameter and length. The work provides an innovative idea for solving the vegetable's non-contact measurement problems and can promote the application of computer vision in agricultural automation.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available