基于TRIZ的蓝莓病害检测方法
Trials(2020)SCI 4区
Abstract
为克服蓝莓采后人工分拣的弊端,提升蓝莓自动分拣的水平,提出利用TRIZ理论中发明原理,构建物质—场模型,结合高光谱成像技术应用物理效应和现象研究一种蓝莓病害的无损检测方法.首先应用TRIZ理论中机械系统替代原理利用高光谱成像系统获取蓝莓高光谱图像、物理参数改变原理提出了基于光谱数据分割蓝莓图像的光谱信息分割法SIS.通过与传统的阈值分割方法对比分析可知,SIS分割法更能准确分割出蓝莓及其病害区域.通过分析蓝莓病害区域与正常区域的光谱曲线的差异,将全波段光谱分成可见光第一区域波段(500~760nm)和近红外第二区域波段(760~1000nm),应用TRIZ理论中组合原理将特征波段提取IRIV法与CARS法结合为CARS-IRIV法提取出第一区域与第二区域组合的7个特征波长(500,522,701,828,857,893,969nm).最后将不同区域的特征波长对应的光谱反射率以及两个区域特征波长结合对应的光谱反射率作为径向基神经网络RBF模型的输入矢量建立蓝莓病害检测模型.试验结果表明第一区域与第二区域组合提取的特征波长对应的光谱反射率作为RBF模型的输入矢量检测蓝莓病害结果最好,正确检测率达到87% 以上.试验结果说明基于TRIZ理论提出的SIS-CARS-IRIV-RBF模型能够更有效地检测蓝莓腐烂病害,可为蓝莓在线实时分拣、提高蓝莓行业自动化水平和生产效益提供一定的理论基础和技术支撑.
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