摘要
建立基于连续投影算法(successive projections algorithm,SPA)-多元线性回归(multiple linear regression,MLR)-受试者特性(receiver operating characteristic,ROC)分析鸡胴体表面稀释污染物识别方法。首先采用高光谱成像系统获取了20个涂有稀释污染物的鸡胴体图像,再利用SPA从1 232个波长中提取出10个特征波长,然后通过MLR方法构建识别函数和特征波长光谱值之间的回归模型,最后通过ROC分析方法,确定出能够获得高真阳性率(true positive rate,TPR)和低假阳性率(false positive rate,FPR)的最佳分类阈值,并据此对鸡胴体表面稀释后的污染物进行检测。结果显示,利用SPA-MLR-ROC分类器检测20个污染鸡胴体样本,检出污染区域的TPR达到98.08%,FPR仅为0.39%,高于波段比算法以及双波段算法检测相同样本的准确率,可见,SPA-MLRROC分类器方法检测鸡胴体表面稀释污染物获得了较好的效果,但由于样本数量有限,还需要具有较大样本量的研究来进一步验证此方法检测结果的稳定性。
This paper presents a method for the identification of diluted contaminants on the surface of chicken carcasses based on successive projections algorithm（SPA）-multiple linear regression（MLR）-receiver operating characteristic（ROC） classifier.Firstly,a total of 20 images of carcasses with diluted contaminants were acquired by hyperspectral imaging system,and 10 characteristic bands were extracted from the 1 232 bands by SPA.Then the MLR method was used to construct a regression model between the discriminant function and the characteristic spectral bands.Finally,the optimal classification threshold with high true positive rate（TPR） and low false positive rate（FPR） was determined by ROC analysis.Thus,the SPA-MLR-ROC classifier allowed the identification of the diluted contaminants.The results showed that the TPR of the SPA-MLR-ROC classifier was 98.08% and the FPR was only 0.39%.The detection accuracy was higher than that of the band ratio algorithm and the dual-band algorithm.Hence,the SPA-MLR-ROC classifier exhibited good performance for the detection of diluted contaminants on the surface of chicken carcass.However,because of the limited number of samples,further study using more samples is needed to verify the stability and feasibility of this method.
出处
《食品科学》
EI
CAS
CSCD
北大核心
2017年第24期247-252,共6页
Food Science
基金
江苏省科技支撑计划项目(BE2014708)
中央高校基本科研业务费专项(KYZ201665)
关键词
连续投影-多元线性回归-受试者特性分析
分类器
污染物
高光谱图像
鸡胴体
successive projections algorithm-multiple linear regression-receiver operating characteristic analysis
classifier
contaminants
hyperspectral imaging
chicken carcass
