Computer Engineering and Applications ›› 2010, Vol. 46 ›› Issue (35): 202-204.DOI: 10.3778/j.issn.1002-8331.2010.35.058

• 图形、图像、模式识别 • Previous Articles     Next Articles

Apple grading detection based on fusion of shape and color features

LI Xian-feng1,2,ZHU Wei-xing1,HUA Xiao-peng2,KONG Ling-dong2   

  1. 1.School of Electronic and Information Engineering,Jiangsu University,Zhenjiang,Jiangsu 212013,China
    2.School of Information Engineering,Yancheng Institute of Technology,Yancheng,Jiangsu 224051,China
  • Received:2010-06-21 Revised:2010-08-27 Online:2010-12-11 Published:2010-12-11
  • Contact: LI Xian-feng

融合形状和颜色特征的苹果等级检测

李先锋1,2,朱伟兴1,花小朋2,孔令东2   

  1. 1.江苏大学 电气信息工程学院,江苏 镇江 212013
    2.盐城工学院 信息工程学院,江苏 盐城 224051
  • 通讯作者: 李先锋

Abstract: In order to increase the accuracy and stability of apple grading,shape and color features which can show the apple’s appearance quality are separately extracted by Fourier descriptor and HIS color model.Firstly,the apples are graded respectively by neural network.Then,the former grading results are used as evidences to achieve the decision fusion.Finally,using identification threshold to get the grades.The experimental results show that the grading accuracy reaches 93.75%,the proposed method has good performance on accuracy and stability compared to the grading method based on single feature.

Key words: D-S evidence theory, feature extraction, Fourier descriptor, HIS model, decision fusion, apple grading

摘要: 为了提高苹果分级的准确率和稳定性,在图像处理的基础上,基于Fourier描述子和HIS颜色模型分别提取了苹果的形状和颜色两类主要外观特征,并分别用神经网络进行单特征初步分级,将其结果作为证据,通过D-S证据理论进行决策级融合,根据分类阈值得到最终分级结果。实验结果表明,该方法分级正确率达93.75%,与单指标特征分级相比,识别率高,稳定性好。

关键词: D-S证据理论, 特征提取, 傅里叶描述子, HIS模型, 决策级融合, 苹果分级

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