MATEC Web Conf.
Volume 232, 20182018 2nd International Conference on Electronic Information Technology and Computer Engineering (EITCE 2018)
|Number of page(s)||5|
|Section||Algorithm Study and Mathematical Application|
|Published online||19 November 2018|
Research on the tea bud recognition based on improved k-means algorithm
School of Mechanical and Automotive Engineering, Shanghai University of Engineering Science, China
a Corresponding author: Wu Minghuiwmhui@yeah.net
The identification and extraction of tea buds is the key technology for the development of automated tea picking robots. Machine vision technology is an effective tool for tea bud recognition. In this paper, the tea tree leaves in the tea garden picking period are taken as research objects, and the research experiments are carried out from the aspects of tea image collection, image enhancement, image segmentation, edge detection, binarization and foreground extraction. After continuous exploration and research, the HSI color model is finally selected. After the S factor was used to grayscale the tea image, the improved K-means algorithm was used to identify and separate the tea shoots. The experimental results show that the improved K-means algorithm has a good effect on the segmentation of young leaves in tea images. This study can provide reference and reference for tea bud recognition algorithm.
© The Authors, published by EDP Sciences, 2018
This is an open access article distributed under the terms of the Creative Commons Attribution License 4.0 (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.