A Machine Vision-Based Method for Tea Buds Segmentation and Picking Point Location Used on a Cloud Platform

文献类型： 外文期刊

第一作者： Lu, Jinzhu

作者： Lu, Jinzhu;Yang, Zhiming;Lu, Jinzhu;Yang, Zhiming;Sun, Qianqian;Gao, Zongmei;Ma, Wei

作者机构：

关键词： tea buds picking; deep learning; image segmentation; cloud platform

期刊名称：AGRONOMY-BASEL （ 影响因子：3.7； 五年影响因子：4.0 ）

ISSN：

年卷期： 2023 年 13 卷 6 期

页码：

收录情况： SCI

摘要： The segmentation and positioning of tea buds are the basis for intelligent picking robots to pick tea buds accurately. Tea images were collected in a complex environment, and median filtering was carried out to obtain tea bud images with smooth edges. Four semantic segmentation algorithms, U-Net, high-resolution network (HRNet_W18), fast semantic segmentation network (Fast-SCNN), and Deeplabv3+, were selected for processing images. The centroid of the tea buds and the image center of the minimum external rectangle were calculated. The farthest point from the centroid was extracted from the tea stalk orientation, which was the final picking point for tea buds. The experimental results showed that the mean intersection over union (mIoU) of HRNet_W18 was 0.81, and for a kernel with a median filter size of 3 x 3, the proportion of abnormal tea buds was only 11.6%. The average prediction accuracy of picking points with different tea stalk orientations was 57%. This study proposed a fresh tea bud segmentation and picking point location method based on a high-resolution network model. In addition, the cloud platform can be used for data sharing and real-time calculation of tea bud coordinates, reducing the computational burden of picking robots.

分类号：

  • 相关文献
作者其他论文 更多>>

微信小程序