魏英姿,谭龙田,谷侃锋,杨继兰,曹雪萍.玉米籽粒激光切片定位技术[J].农业机械学报,2019,50(1):35-41.
WEI Yingzi,TAN Longtian,GU Kanfeng,YANG Jilan,CAO Xueping.Clustering Method of Positioning for Maize Seed Laser-cutting Slices Combined with Spatial Constrains[J].Transactions of the Chinese Society for Agricultural Machinery,2019,50(1):35-41.
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玉米籽粒激光切片定位技术   [下载全文]
Clustering Method of Positioning for Maize Seed Laser-cutting Slices Combined with Spatial Constrains   [Download Pdf][in English]
投稿时间:2018-07-19  
DOI:10.6041/j.issn.1000-1298.2019.01.003
中文关键词:  玉米籽粒  激光切片  定位  相关性滤波器  二分均值聚类
基金项目:辽宁省自然科学基金项目(20180550791、20180550520)和辽宁省教育厅高等学校基本科研项目(LG201708)
作者单位
魏英姿 沈阳理工大学 
谭龙田 沈阳理工大学 
谷侃锋 中国科学院沈阳自动化研究所 
杨继兰 沈阳理工大学 
曹雪萍 沈阳理工大学 
中文摘要:玉米籽粒形态各异、尺寸不一,精确定向和定位玉米籽粒的激光切片是实现高通量全自动玉米分子育种基因型分析的关键。应用机器视觉技术从玉米籽粒图像中准确识别玉米籽粒的特征区,以期实现上述操作。为描述像素所在空间的相关信息,设计一种相关面积占比滤波器。定义圆形掩模模板,根据单玉米籽粒的面积,确定模板尺寸。利用圆形模板筛选像素点数据,得到待分类数据集合。通过指定初始聚类中心,对数据执行二分均值聚类,得到尖端类和两个大端外凸角类的聚类中心。通过贴标签运算精选连通域,校正聚类中心的位置,生成尖端和大端外角特征区的精确标记。依据大端外凸角附近的两组插值点对,得到激光切割线的位置,利用尖端类定位点和玉米籽粒形心定位点确定玉米籽粒的夹持位姿。与SUSAN检测方法对比,表明了本文方法的有效性。
WEI Yingzi  TAN Longtian  GU Kanfeng  YANG Jilan  CAO Xueping
Shenyang Ligong University,Shenyang Ligong University,Shenyang Institute of Automation, Chinese Academy of Sciences,Shenyang Ligong University and Shenyang Ligong University
Key Words:maize seed  laser-cutting slices  positioning  correlation filter  bisecting means clustering
Abstract:Maize seeds are of different shapes and sizes. It is the bottleneck that the maize seed laser cutting slices are orientated and positioned accurately for the molecular breeding genotype analysis to achieve high throughput with automation. The machine vision system means to recognize the maize feature regions for positioning laser cutting slices accurately in a single seed image. An area correlation filter was presented for describing the pixel with spatial constrain information. The definition of the round mask template was proposed for the seed morphological measurement. The round template size was determined by the area of a single maize seed. Some of pixel coordinate data were extracted to be classified from the target domains by the filtration of the area correlation filter. Through the bisecting means clustering with the specific initial clustering centers, the extracted data were divided into thin part class and thick part class. Also, their clustering centers were got, which were corresponded to the thin part class and two arc corner classes, respectively. The labeling partition operation was applied to the connected domains for finely adjusting and marking the centers of tip part and two arc corners. Finally, the coordinates of two interpolated point pairs near the thick part were calculated. Through linking two pairs of interpolated points, the laser cutting lines were located with high precision. The seed clamping pose was determined according to the tip part center and the centroid of seed. Compared with SUSAN, SUSAN detector cannot be directly applied to locate the feature region of maize seed. The experimental results verified the effectiveness of the proposed method on yellow and white maize seeds.

Transactions of the Chinese Society for Agriculture Machinery (CSAM), in charged of China Association for Science and Technology (CAST), sponsored by CSAM and Chinese Academy of Agricultural Mechanization Science(CAAMS), started publication in 1957. It is the earliest interdisciplinary journal in Chinese which combines agricultural and engineering. It always closely grasps the development direction of agriculture engineering disciplines and the published papers represent the highest academic level of agriculture engineering in China. Currently, nearly 8,000 papers have been already published. There are around 3,000 papers contributed to the journal each year, but only around 600 of them will be accepted. Transactions of CSAM focuses on a wide range of agricultural machinery, irrigation, electronics, robotics, agro-products engineering, biological energy, agricultural structures and environment and more. Subjects in Transactions of the CSAM have been embodied by many internationally well-known index systems, such as: EI Compendex, CA, CSA, etc.

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