Cane bud recognition and positioning method based on machine vision
Authors: 
JiaoDi Liu, XuTing Liu, HuaiAn Yi, Kun Zhong, Jiawen LiAuthors Info & Claims
Pages 482 - 485
Abstract
In order to realize sugarcane bud orientation and positioning seeding, a sugarcane bud tracking and positioning method based on improved GOTURN algorithm is proposed. This method takes the segmented image of sugarcane in natural environment as the object, and uses YCbCr color space to convert the image into binary value. After a series of morphological treatments of expansion and corrosion, the area of the cane bud is obtained by frame selection. Finally, the sugarcane bud is tracked by the GOTURN algorithm, and the width of the frame of the cane bud frame is compared at different angles to define the minimum width of the cane bud For qualified positioning. In this way, the continuous and dynamic intelligent recognition of sugarcane seed characteristics by the sugarcane seeding device is realized.
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Index Terms
- Cane bud recognition and positioning method based on machine vision
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Information
Published In
April 2020
640 pages
ISBN:9781450376457
DOI:10.1145/3436286
- Conference Chairs:
- M. James C. Crabbe,
- Rita Yi Man Li,
- Rebecca Kechen Dong,
- Otilia Manta,
- Ubaldo Comite
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Association for Computing Machinery
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Published: 04 January 2021
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ISBDAI '20
ISBDAI '20: 2020 2nd International Conference on Big Data and Artificial Intelligence
April 28 - 30, 2020
Johannesburg, South Africa
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Overall Acceptance Rate 70 of 340 submissions, 21%
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