基于高光谱和频谱特征的注水肉识别方法

Identification of Water Injection Meat Based on Hyperspectral Technique and Spectrum Characteristics

为实现注水肉快捷有效的识别,以猪肉为研究对象,利用高光谱技术分析了注水肉和正常肉的光谱特征,通过傅里叶变换的方法,提取样本的频谱特征参数,然后分别基于猪肉样本的全光谱、特征光谱和频谱特征参数,分别建立正常猪肉和注水猪肉的支持向量机(SVM)和BP神经网络分类识别模型,并采用验证集对模型性能进行试验验证。结果表明,基于频谱特征参数建立的神经网络分类识别模型具有最优的分类识别效果,正确识别率达98.8%;基于特征光谱建立的神经网络分类识别模型分类识别效果次之,正确识别率为96.4%;而基于全光谱建立的支持向量机分类识别模型分类识别效果最差,正确识别率只有84.5%。说明采用高光谱技术可以对注水猪肉进行快速而有效的检测识别。

To quickly and effectively identify water injection meat,the spectral characteristics of water injection and normal meat were analyzed through the hyperspectral analysis technology.The spectrum characteristic parameters of every sample were obtained by using the Fourier transform and statistical calculation.Then the support vector machine(SVM)and neural network(BP)classification models were developed based on the full spectrum,characteristic spectrum and spectrum characteristic parameter,respectively.Finally,the two models were validated by an independent validation set and three indicators such as product’s accuracy(PA),user’s accuracy(UA)and overall accuracy(OA)were used to test the model performance.The results showed that the neural network classification recognition model based on spectrum characteristic parameters had optimal classification recognition rate for water injection pork,with the correct recognition rate of 98.8%.The neural network classification and recognition model based on the characteristic spectrum had the second best recognition,with the correct recognition rate of 96.4%.The classification recognition model of SVM based on full spectrum had the worst classification and recognition for water injection pork,and its correct recognition rate was only 84.5%.These results suggest that hyperspectral technique can be used for rapid and effective detection and identification of watered-down pork.