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浙江大学学报(工学版)
J4  2009, Vol. 43 Issue (5): 869-871    DOI: 10.3785/j.issn.1008-973X.2009.05.016
自动化技术、计算机技术     
水果按表面颜色分级的方法
饶秀勤,应义斌
（浙江大学 生物系统工程与食品科学学院,浙江 杭州 310029）
Grading a fruit by it's surface color
 RAO Xiu-Qi, YING Xi-Bin
(College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou 310029, China)
 全文: PDF(598 KB)   HTML
摘要：

为提高水果商品品质,提出了一种基于水果表面颜色的分级方法.将完成图像分割的水果图像转换为HIS颜色模型,提取其H分量的面积加权直方图并对其进行了主成分分析,以红色水果样本组和橙色水果样本组的前M个主成分均值作为这两个样本组的样本中心点建立分级模型.分别计算待测样本与这两个样本中心点的马氏距离值,当待测样本到红色水果样本组样本中心点的马氏距离值小于其到橙色水果样本组样本中心点的马氏距离值时,将其分级到红色水果样本组,否则分级到橙色水果样本组.对800幅脐橙图像进行了分类试验,发现采用水果图像H分量面积加权直方图的前两个主成分分量进行分析即可实现水果分级,总的分级误差仅为1.75%.
Abstract:

A grading method was developed to improve the quality of fruits. HIS color model was introduced to analyze the fruit image after segmentation. The principal component  (PC) of the H component histogram weighted by the fruit surface area was calculated. And then the average values of the most significant M PCs of the red and yellow sample  groups were calculated respectively, which were used as the centers of the two sample groups to setup a grade model. A fruit was graded to the red group if the Mahalanobis  distance between the fruit and the center of the red sample group was less than that between the fruit and the center of the yellow group, or it was graded to the yellow group.  The test results of 800 navel orange images showed that  the first and the second PCs of the H component histogram weighted by the fruit surface area were enough to grade a  fruit, and the total error was only 1.75%．
出版日期: 2009-11-18
:  S37  
基金资助:

国家科技支撑计划资助项目（2006BAD10A）.
通讯作者: 应义斌，男，教授.     E-mail: ybying@zju.edu.cn
作者简介: 饶秀勤（1968-），男，湖北天门人，副教授，从事农产品品质快速检测的机器视觉技术研究.
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引用本文:

饶秀勤, 应义斌. 水果按表面颜色分级的方法[J]. J4, 2009, 43(5): 869-871.

RAO Xiu-Qi, YING Yi-Bin. Grading a fruit by it's surface color. J4, 2009, 43(5): 869-871.

链接本文:

http://www.zjujournals.com/eng/CN/10.3785/j.issn.1008-973X.2009.05.016    或    http://www.zjujournals.com/eng/CN/Y2009/V43/I5/869

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