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基于数字图像的茶叶形状特征提取及不同茶叶鉴别研究

  • 陆江锋 ,
  • 单春芳 ,
  • 洪小龙 ,
  • 裘正军
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  • 1. 浙江大学生物系统工程与食品科学学院,浙江 杭州 310029;
    2. 网迅(中国)软件有限公司,浙江 杭州 310012
陆江锋(1985— ),男,浙江东阳人,主要从事农业信息化方向的研究。

收稿日期: 2010-03-23

  修回日期: 2010-07-14

  网络出版日期: 2019-09-11

基金资助

国家自然科学基金(30600371)、教育部重点项目(109090)、浙江省自然科学基金(Y3080277)

Shape Extraction and Varietial Discrimination of Tea Based on Digital Image

  • LU Jiang-feng ,
  • SHAN Chun-fang ,
  • HONG Xiao-long ,
  • QIU Zheng-jun
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  • 1. College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou 310029, China;
    2. WebEx (China) Software Co., Hangzhou 310012, China

Received date: 2010-03-23

  Revised date: 2010-07-14

  Online published: 2019-09-11

摘要

研究了茶叶图像处理的关键技术和方法,包括茶叶图像的阈值变换、中值滤波、图像标记、边界轮廓跟踪等,解决了茶叶外形特征参数的快速准确提取和计算;设计了基于数字图像处理的茶叶外形特征检测软件,实现了茶叶图像的实时采集、图像预处理、特征参数提取等功能;最后运用该软件提取3种不同茶叶样品共108片茶叶图像的17项外形特征参数,并以其中6项参数作为BP神经网络的输入,建立不同茶叶样品与外形特征之间的BP神经网络预测模型,并对30片未知茶叶样本进行预测,鉴别准确率达到80%。

本文引用格式

陆江锋 , 单春芳 , 洪小龙 , 裘正军 . 基于数字图像的茶叶形状特征提取及不同茶叶鉴别研究[J]. 茶叶科学, 2010 , 30(6) : 453 -457 . DOI: 10.13305/j.cnki.jts.2010.06.008

Abstract

The key methods of tea image processing were studied, including threshold transforming, median filter, image mark and boundary following. These methods solved the problem of how to accurately extract and calculate the characteristic parameters of tea shape. The software for tea quality detection based on digital image was developed. The functions, such as collection of tea image, image processing and extraction of characteristic parameter, could be accomplished. Using the software, 17 shape characteristic parameters were collected from 108 pieces of three different kinds of tea. And 6 characteristic parameters were used to build the back propagation-artificial neural network (BP-ANN) model. The variety from thirty unknown samples were predicted by this model and the recognition rate of eighty percent was achieved.

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