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基于颜色特征的草莓成熟度识别技术研究
引用本文:赵玲,周桂红.基于颜色特征的草莓成熟度识别技术研究[J].河北农业大学学报,2017,40(2).
作者姓名:赵玲  周桂红
作者单位:河北农业大学 信息科学与技术学院,河北 保定,071001
基金项目:河北农业大学理工基金项目
摘    要:草莓成熟度识别技术是草莓采摘机器人顺利完成采摘任务的关键。本研究以"丰香"草莓为研究对象,首先提取不同成熟度草莓的颜色特征,计算草莓图像在HIS颜色空间模型下H分量的均值和方差;然后计算草莓果实红色部分着色面积所占比例;最后,建立BP神经网络,以H分量的均值、方差和草莓红色着色面积比作为BP神经网络的输入,训练完成后,判断待测样本的成熟度等级。通过本研究实验方法划分成熟度等级与经验丰富的果农判断结果对比,实验正确率可以达到90%以上。

关 键 词:草莓  成熟度  颜色特征提取  着色面积  BP神经网络

Study on recognition technology of strawberry maturity based on color feature
ZHAO Ling,ZHOU Gui-hong.Study on recognition technology of strawberry maturity based on color feature[J].Journal of Agricultural University of Hebei,2017,40(2).
Authors:ZHAO Ling  ZHOU Gui-hong
Abstract:For the strawberry harvesting robot,identification technology of strawberry maturity is one of the key technologies.In this paper,"Feng Xiang" strawberry was taken as the research object,The color characteristics of strawberry with different maturity degrees were extracted,and the mean and variance of the H component were calculated in the HIS color space model.Then the proportion of the red part of the color area was calculated.Finally,the BP neural network was established,taking the mean value,variance of H component and red coloration area ratio of strawberry as the inputs of BP neural network.After the training process being completed,the maturity grade of the tested sample was validated.Compared with the judging result of experienced strawberry farmers,the experimental accuracy is above 90%.
Keywords:strawberry  maturity  color feature extract  colored area  BP neural network
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