摘要
针对单特征苹果分级的不确定性和低正确率,通过图像处理提取大小、形状、颜色和缺陷4类能反映苹果外观品质的主要特征,引入信息融合的思想,以单特征初步分级的结果作为证据,用D-S证据理论的方法进行决策级融合处理,实现苹果的多特征综合分级,进一步提高可靠性和分级正确率。80个测试样本的分级试验表明,苹果分级正确率达92.5%,与单特征分级相比,此方法正确识别率高、稳定性好、效果显著。
According to the uncertainty and low accuracy of apple grading relying on the single feature,key features such as size,shape,color and defect which could show the apple＇s appearance quality were extracted and a decision fusion method based on D-S evidence theory was proposed.Firstly,the apples were graded according to each of the four features utilizing human experience and neural network.Then,the former grading results were used as evidences to achieve the decision fusion in order to increase the grading reliability and accuracy.Finally,80 apple samples were used to test grading effect.The experimental results showed that five apples were misjudged and the grading accuracy reached to 92.5%.The proposed method had good performance on classification rate and stability compared to the grading method based on single feature.
出处
《农业机械学报》
EI
CAS
CSCD
北大核心
2011年第6期188-192,共5页
Transactions of the Chinese Society for Agricultural Machinery
基金
盐城工学院重点建设学科开放基金资助项目(XKY2010021)
