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机器视觉技术在金莲花灌溉中的应用研究
引用本文:宋亚杰,谢守勇.机器视觉技术在金莲花灌溉中的应用研究[J].西南农业大学学报,2006,28(4):659-662.
作者姓名:宋亚杰  谢守勇
作者单位:西南大学工程技术学院,重庆400716
基金项目:重庆市中青年骨干教师资助项目
摘    要:应用机器视觉技术研究了判断作物缺水状态的方法。在日光条件下采集了金莲花叶片图像,然后分别提取了红绿蓝(RGB)三色分量和它们的相对系数rgb及色度H。在RGB和HSI颜色模型下分析了各分量与作物缺水时间之间的相关特性.分析结果表明红色分量R、绿色分量G、蓝色分量B、以及r分量、b分量都与缺水时间之间有相当高的相关性,可以用作利用机器视觉快速判断金莲花缺水状况的指标,而其他分量与缺水时间之间没有明显的相关性。

关 键 词:机器视觉  图像处理  金莲花  灌溉
文章编号:1000-2642(2006)04-0659-04
收稿时间:06 15 2006 12:00AM
修稿时间:2006-06-15

APPLICATION OF MACHINE VISION IN THE IRRIGATION FOR TROPAEOLUM
SONG Ya-jie,XIE Shou-yong.APPLICATION OF MACHINE VISION IN THE IRRIGATION FOR TROPAEOLUM[J].Journal of Southwest Agricultural University,2006,28(4):659-662.
Authors:SONG Ya-jie  XIE Shou-yong
Institution:College of Engineering and Technology, Southwest University, Chongqing 400716, China
Abstract:The images of Tropaeolum leaves were taken under sunlight, and the red ( R) , green ( G) and blue ( B ) and their relative ratios (rgb) and the hue of the images were calculated. The RGB and HIS models were used to analyze the correlation of the color parameters and water requirement of the leaves. Highly significant linear correlation was found to exist between R, G, B, r and b, on the one hand, and water requirement of the leaves, on the other. Therefore, these parameters can be used as indices for fast diagnosis of water deficiency using machine vision. No obvious correlation was found between leaf water deficiency and other parameters studied.
Keywords:machine vision  image processing  Tropaeolum  irrigation
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