摘要
国内外关于马铃薯品质检测的机器视觉分级技术研究甚少,马铃薯单薯质量是马铃薯的重要指标。为此,通过对马铃薯图像进行预处理,提取相关特征参数,采用逐步回归分析方法对多个特征参数进行分析和筛选,用马铃薯俯视和侧视投影图像中的面积参数构建了单薯质量模型。利用该模型对300个马铃薯进行了检验,结果表明:该方法提取的参数个数少且检测误差小,满足了生产的需要。
Potato quality detection in China remains at the stage of dependent on human sense organ to identify and judge. Single potato weight is an important grade indicator. In this paper, the characteristic features were obtained through image preprocessing and the stepwise regression analysis method. A model for potato weight detecting based on its area features was setup. This method was of higher accuracy, better efficiency and could be applied to practical potato grading.
出处
《农机化研究》
北大核心
2009年第9期61-63,共3页
Journal of Agricultural Mechanization Research
关键词
机器视觉
马铃薯质量检测
面积特征
machine vision
potatoes weight detection
area feature
