基于外部特征信息的蟠桃质量预测模型

采用计算机图像处理技术对蟠桃的缝合中线处直径、与缝合中线垂直处的直径以及厚度3个几何特征参数进行分析,建立基于外部特征信息的蟠桃质量预测模型。通过多元线性回归方法拟合出实测值与蟠桃质量的预测模型,比较不同参数所得模型的拟合优度,找到最优质量预测模型。通过将MATLAB R2014a软件获取的像素值与相应几何参数进行拟合,最终得到像素质量预测模型,预测准确率达到91.87%。结果表明:基于外部特征信息的蟠桃质量预测研究是可行的,可为采用机器视觉方法进行蟠桃质量分级提供依据。

Prediction model of flat peach-mass based on external characteristic information

Using the computer image processing technology to analyze three geometric parameters of the flat peach (i.e. the diameter of flat peach in the suture midline, the diameter perpendicular to the suture midline and the thickness). The prediction model of flat peach-mass was established based on external characteristic information. And through the analysis of multiple linear fitting, found the prediction model of the measured values and flat peach-mass. By comparing goodness of fit of different models based on different parameters, the optimal quality prediction model was established. The MATLAB R2014a software acquired the pixel value of the corresponding geometric parameter. The pixel-mass prediction model was founded by fitting with it. The results suggest that predicting flat peach-mass based on external characteristic information is practicable. The study provides the basis for the use of machine vision method to classify flat peach-mass.