Research on key quality of sausage with SVM and hyperspectral imaging full scale features

摘要

In this paper a quick and accurate detection method is proposed, which can identify whether the sausage contains excessive acid value, peroxide value and area of colony. By using hyperspectral image measurement and multi-information fusion based on support vector machine (SVM), the sausage content model is established. In order to improve the accuracy of hyperspectral image measurement predicted model and to reduce the measurement turbulence, the image information and the NIR value data that are input as the parameters of the hyperspectral image content model are introduced. The detection model's RMSECV and r of the research are 0.251 and 0.972. The study concludes that the theory and method can be further extended to the detection of other related meat agricultural products.