Prediction of Moisture Content for Congou Black Tea Withering Leaves Using Image Features and Nonlinear Method.

ABSTRACT: Withering is the first step in the processing of congou black tea. With respect to the deficiency of traditional water content detection methods, a machine vision based NDT (Non Destructive Testing) method was established to detect the moisture content of withered leaves. First, according to the time sequences using computer visual system collected visible light images of tea leaf surfaces, and color and texture characteristics are extracted through the spatial changes of colors. Then quantitative prediction models for moisture content detection of withered tea leaves was established through linear PLS (Partial Least Squares) and non-linear SVM (Support Vector Machine). The results showed correlation coefficients higher than 0.8 between the water contents and green component mean value (G)

SUBMITTER: Liang G 

PROVIDER: S-EPMC5959864 | biostudies-literature | 2018 May

REPOSITORIES: biostudies-literature