期刊论文

中文

中国农业科学

0578-1752

2008

41

11

3741-3745

湖南省教育厅科学研究项目（06D059）

本校为其他机构

【目的】研究涟红温州蜜柑pH的机器视觉检测及影响检测精度的因素。【方法】对机器视觉系统采集的柑橘图像进行图像裁切、RGB空间至HSI空间的转换和差值法去图像背景,用色调H和饱和度S为输入,建立小波神经网络柑橘pH预测模型,无损检测柑橘pH。【结果】30个测试样本的检测结果表明,预测偏差最大值为9.95%、偏差最小值为-3.6%、平均偏差为0.8%、标准偏差为2.95%,pH±0.1精度内的正确识别率为80%,pH±0.2精度内的正确识别率为93.33%。【结论】涟红温州蜜柑pH与果皮色泽之间具有相关性,可用机器视觉检测其pH。但进一步提高预测精度,首先须在图像处理环节上去除各种虫斑与病斑的影响。

[Objective] pH value measuring method of ＇Lianhong＇ citrus fruits based on machine vision and factors influencing measurement accuracy were studied. [ Method ] Images of citrus fruits from machine vision system were processed by cutting, converting from RGB space to HSI space, removing background by deviation. A wavelet neural network model was constructed to detect pH value of citrus fruits non-destructively, the inputs of the model were image hue H and saturation S. [ Result ] Results of test of 30 samples showed that the maximal deviation ...