摘要
采用机器视觉技术,针对新疆无核白葡萄干的颜色特征进行分级研究,提取HIS颜色图像,采用中值滤波法滤波,采用最大类间方差法分割图像,采用形态学开运算去除二值图像中的伪目标区域,获得最佳二值图像。同时,分析色调灰度直方图和颜色矩均值直方图,确定采用H、S、I分量颜色的一阶矩、二阶矩、三阶矩作为特征值建立BP神经网络的色泽分级模型,分级准确率最高为96.42%。
The object of this study is to grade color features of xinjiang thompson seedless raisins ,extracting the HSI im-age,median filtering method is used to filter the noise ,OTSU method is used for image segmentation ,morphological open operation is used to remove the false target area in the binary image ,so that we can get the best binary image .Analysising the tonal cumulative gray histogram and color moments histogram is used to determine the first moment ,second moment and the third moment of H,S,I color components,color moments are as characteristic values to establish the BP neural network classification model ,the highest classification accuracy is 96 .42%.
出处
《农机化研究》
北大核心
2015年第5期24-28,共5页
Journal of Agricultural Mechanization Research
基金
国家自然科学基金项目(61367001)
新疆农业工程装备创新设计重点实验室资助项目(2013-2017)
关键词
机器视觉
图像处理
无核白葡萄干
人工神经网络
颜色分级
machine vision techniques
imaging processing
thompson seedless raisins
BP neural network
color classi-fication