文章基本信息

标题：Research on the tea bud recognition based on improved k-means algorithm
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作者：Peidi Shao ; Minghui Wu ; Xianwei Wang 等
期刊名称：MATEC Web of Conferences
电子版ISSN：2261-236X
出版年度：2018
卷号：232
DOI：10.1051/matecconf/201823203050
语种：English
出版社：EDP Sciences
摘要：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.