南京林业大学学报(自然科学版) ›› 2009, Vol. 33 ›› Issue (01): 136-138.doi: 10.3969/j.jssn.1000-2006.2009.01.029

• 研究简报 • 上一篇    下一篇

基于神经网络的苹果自动分级方法

赵茂程,侯文军   

  1. 南京林业大学机械电子工程学院,江苏南京210037
  • 出版日期:2009-02-18 发布日期:2009-02-18
  • 基金资助:
    收稿日期:2007-11-01修回日期:2008-05-06 基金项目:江苏省“青蓝工程”一般学科带头人培养对象资助项目;常州市科技攻关项目(CE2004206);南京林业大学“十五”人才基金资助项 目作者简介:赵茂程(1966—),教授,博士,研究方向为图像处理、检测技术及自动化装置。Email:mczhao@njfu.com.cn 引文格式:赵茂程,侯文军.基于神经网络的苹果自动分级方法[J].南京林业大学学报:自然科学版,2009,33(1):136138.

Method of apple automatic grading based on neural network

ZHAO Maocheng,HOU Wenjun   

  1. College of Electronic and Mechanical Engineering, Nanjing Forestry University, Nanjing 210037, China
  • Online:2009-02-18 Published:2009-02-18

摘要: 用HSI模型描述苹果颜色特征,根据苹果颜色直方图特点,采用4个色度均值代替苹果色度值。在此基础上,建立了BP神经网络水果分级系统 ,该系统输入层由4个节点组成,隐含层由5个节点组成,输出层由2个节点组成。试验结果表明:该系统的分级正确率为95%,可以满足生产需要 。

Abstract: The HSI color model was used to describe the color feature of the apple in the paper. Four chroma average values were used to substitute the apple chroma from the apple color histogram. The apple grading system based on BP neural network was established. In the system, there were 4 nodes of chroma in the input layer, 2 nodes of apple types in the output layer and 5 nodes in the implicit layer. The experimental results showed that 95% apples could be graded precisely and the system could meet practical demands.

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