Detection Method for the Buds on Winter Vines Based on Computer Vision

Sheng Xu, Y. Xun, Tingmeng Jia, Qinghua Yang
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引用次数: 16

Abstract

According to the requirement of grape pruning in winter, an algorithm of detecting the buds of grape vines based on machine vision was proposed, laying the foundation of grape vines automotive pruning. The grapevines' color image was captured indoor. The blue component of the color image was selected for the image preprocessing such as filter, threshold segmentation and noise removal. After that a binary image was gained. With the binary image, Rosenfeld algorithm was used in thinning to extract the skeleton of the grape branches. Because the morphological characteristic of the buds was similar to the corners, Harris algorithm was chosen to detect the point of buds from the skeleton image. The experiment result showed that it's effective to detect the buds with the strategy of this paper. The recognition rate reached 70.2%.
基于计算机视觉的冬藤芽检测方法
根据冬季葡萄修剪的要求,提出了一种基于机器视觉的葡萄藤芽检测算法,为葡萄藤自动修剪奠定了基础。葡萄藤的彩色图像是在室内拍摄的。选取彩色图像中的蓝色分量进行滤波、阈值分割、去噪等图像预处理。然后得到二值图像。利用二值化图像,采用Rosenfeld算法细化提取葡萄枝骨架。由于芽的形态特征与角相似,采用Harris算法从骨架图像中检测芽的点。实验结果表明,本文提出的策略能够有效地检测出花蕾。识别率达70.2%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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