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当前位置: 首页 > 文章 > 基于被动水声信号的淡水鱼混合比例识别 农业机械学报 2019 (1) 215-221
Position: Home > Articles > 基于被动水声信号的淡水鱼混合比例识别 Transactions of the Chinese Society for Agricultural Machinery 2019 (1) 215-221

基于被动水声信号的淡水鱼混合比例识别

作  者：
黄汉英;杨咏文;李路;赵思明;熊善柏;涂群资
单  位：
华中农业大学食品科学技术学院;华中农业大学工学院
关键词：
淡水鱼;被动水声信号;比例识别;主成分分析;支持向量机
摘  要：
针对淡水鱼混合比例识别问题,以鳊鱼和鲫鱼为研究对象,通过水听器采集不同混合比例下的淡水鱼被动水声信号,利用butter函数进行信号预处理,分别提取短时平均能量、短时平均过零率、4层小波包分解频段能量、平均Mel频率倒谱系数、基于功率谱的主峰频率和主峰值等特征,构建特征向量,建立了基于主成分分析的支持向量机混合比例识别模型.分析了不同混合比例的淡水鱼水声信号之间的显著性差异,研究了主成分个数对模型识别率的影响.结果表明,平均Mel频率倒谱系数对淡水鱼混合比例识别效果最优,主成分个数为19时,平均识别正确率为96. 43%,Kappa系数为0. 96.
作  者：
GUO Cailing;LIU Gang;Key Laboratory of Modern Precision Agriculture System Integration Research,Ministry of Education,China Agricultural University;College of Electromechanical Engineering,Tangshan University;Key Laboratory of Agricultural Information Acquisition Technology,Ministry of Agriculture and Rural Affairs,China Agricultural University;
关键词：
apple tree;;canopy;;point cloud extraction;;color sampling;;branch
摘  要：
Construction of 3 D model of tree is a long-term research hotspot in botany,computer graphics,and architecture. And tree canopy branch reconstruction is an important component in the canopy dynamics analysis. The emergence of terrestrial laser scanners has accelerated this reconstruction process. To quickly reconstruct the canopy branch model,it is necessary to delete a large number of nonbranched interference point clouds. Taking the canopy of apple tree in the maturity growth stage as the research object,a method of color-based sampling apple tree canopy trunk point cloud extraction was proposed. Firstly,the apple tree canopy color point cloud acquisition method was proposed. Trimble TX8 and coaxial panoramic camera were selected as the data acquisition device to acquire the apple canopy color point cloud data. Point clouds and color panoramic photos were matched in Realworks software,and color point clouds were get. Then,the color information R,G and B in the panoramic image was extracted. The adaptive segmentation threshold was established according to the distribution rules of R,G and B in the panoramic image branch area. Color point cloud data of the non-branch part in the canopy was deleted according to the threshold. Finally,the 3 D branch model was reconstructed in the Geomgic software. The process was followed by a series of operations,such as wrap,manifold creation,polygon editing,hole filling and smoothing. The experimental results of the apple tree branch extraction point cloud data showed that the point cloud deletion rate of this method was 75. 74%. Compared with the artificial branch point cloud data extraction,the side branch accuracy rate was 93. 34%,and the efficiency was improved by more than 200 times,shortening the three-dimensional reconstruction time of canopy branches. In this way,the results of this study can provide a basis for studying the canopy structure analysis and the establishment of the branching dynamics model of the leafy apple tree.

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