基于BP神经网络的面包工业化生产发酵程度视觉判定

目的:建立BP神经网络模型来实现对面团发酵成熟度的精准判定.方法:利用机器视觉技术采集并处理面包发酵过程的图片,获取图片的量化信息,建立了一种基于BP(back propagation)神经网络的面包发酵程度预测模型.将时间、面积、瞬时速度、膨胀率、灰度值能量、灰度值相互关系、灰度值均匀性、灰度值对比度,作为输入神经元...

Study on visual judgment method of fermentation degree in industrialized bread production based on BP neural network

Objective:A BP neural network model was established to accurately determine the maturity of dough fermentation.Methods:Used machine vision technology to collect and process the pictures of bread fermentation process, obtained the quantitative information of the pictures, and a prediction model was established for bread fermentation degree based on BP neural network. Taking the time, area, instantaneous velocity, expansion rate, gray value energy, gray value relationship, gray value uniformity and gray value contrast as the input neurons, the regression model of relevant parameters was established.Results:The correlation between the above characteristic parameters and the fermentation process of bread was determined, which can effectively characterize the fermentation degree of bread; The results show that the accuracy of the prediction model based on BP neural network is 88.41%.Conclusion:The model can accurately determine the degree of bread fermentation and effectively improve the quality consistency in industrial bread production.