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茶叶科学 ›› 2013, Vol. 33 ›› Issue (6): 584-589.doi: 10.13305/j.cnki.jts.2013.06.015

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基于图像颜色信息的茶叶嫩叶识别方法研究

吴雪梅, 张富贵, 吕敬堂   

  1. 贵州大学机械工程与自动化学院,贵州 贵阳 550025
  • 收稿日期:2013-04-18 修回日期:2013-05-23 出版日期:2013-12-30 发布日期:2019-09-04
  • 作者简介:吴雪梅(1975— ),女,贵州安顺人,副教授,主要从事计算机视觉在农业工程中的应用研究,xm_wu@163.com。
  • 基金资助:
    贵州省科学技术基金项目(黔科合J字[2011]2199号)、贵州大学自然科学青年基金项目[贵大自青基合2009(035)]

Research on Recognition of Tea Tender Leaf Based on Image Color Information

WU Xue-mei, ZHANG Fu-gui, LV Jing-tang   

  1. School of Mechanical Engineering, Guizhou University, Guiyang 550025, China
  • Received:2013-04-18 Revised:2013-05-23 Online:2013-12-30 Published:2019-09-04

摘要: 采集清明时期茶叶图像,获取茶叶的图像信息。论文首先分析了嫩芽与老叶的G和G-B分量的颜色信息,该颜色信息差异能够有效区分嫩芽和背景;然后根据分析结果设定初始阈值,利用改进的最大方差自动取阈法计算G和G-B分量的分割阈值;最后提出了茶叶嫩芽的识别算法。实验结果表明该算法能有效消除光线的影响,快速识别嫩芽;相机与茶树间的距离为10βcm左右时,识别准确率为92%。本研究的方法和结果可为茶叶智能采摘机器的研发提供技术支持。

关键词: 嫩芽, 颜色信息, 图像处理, 识别, 茶叶

Abstract: The images of tea leaf in Qingming period were taken by digital camera for extracting tea color information. Firstly, the color information of G and G-B component of tender leaf and old leaf based on RGB color model was analyzed. The color difference between tender leaf and old leaf was able to distinguish the tender leaf from background. Then the original threshold from color analysis was set and the segmentation thresholds for G and G-B component were calculated by improved Ostu (the algorithm of threshold automatically extracted according to the maximum deviation). Finally, the recognition algorithm of tea tender leaf was proposed. Experimental results showed that the algorithm is useful for eliminating the impact of light and rapid in identifying the tender leaf from background. The accuracy rate is more than 92% when the distance between camera and tea bush is about 10βcm. The research results were useful to provide recognition technical supports for an intelligent picking machine development.

Key words: tender leaf, color information, image processing, recognition, tea

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