超级杂交稻秧盘育秧精密播种性能检测方法及关键技术研究

项目名称： 超级杂交稻秧盘育秧精密播种性能检测方法及关键技术研究

项目编号： No.51505156

项目类型： 青年科学基金项目

立项/批准年度： 2016

项目学科： 机械、仪表工业

项目作者： 谭穗妍

作者单位： 华南农业大学

项目金额： 20万元

中文摘要： 超级杂交稻具有超强的分蘖能力，要求2～3粒/穴低播量精密播种育秧，以保证精准栽插，但由于播种育秧时使用浸泡后发芽的种子，所以播种过程中种子物理特性的变化会影响精密播种器的播种性能。为提高播种性能，本项目应用机器视觉和全景技术，在线动态检测连续输送的播种秧盘，对采集的图像序列进行在线快速的穴播种量检测，并根据检测统计的播种性能变化信息，形成播种量预测信号，及时提供播量智能调节系统；同时，采用图像拼接技术自动地拼接整盘播种图像，预测整盘秧盘播种性能，以及时补种或评价育秧播种器性能。项目在秧盘超级稻种子计数检测算法方面，采用多特征提取技术和特征优选技术，提出基于模式识别检测种子连通区域的颗粒数，并研究将SIFT局部特征应用到稻种连通区域分类识别中，有效地提高多粒种子颗粒数的检测精度，特别适用于重叠、交叉和粘连的情况。本项目研究理论和方法对杂交稻和超级杂交稻精密播种技术具有重要的实际应用价值。

中文关键词： 精密播种机；超级杂交稻；机器视觉；播种量；全景技术

英文摘要： Super hybrid rice is widely cultivated in china. Because super hybrid rice has strong tiller ability, it requires precise and low seeding rate, which need to ensure 2~3 grains each cell in tray plugs. But during the sowing process, some problems arise. Rice seed traits, such as length, shape, moisture, weight change, which greatly affect the performance of seeder sowing machine. As a result, seed distribution on the tray plugs is uneven and sowing quantity changes now and then. To solve the problem, a sowing performance measurement system based on computer vision and panoramic technology is put forward. Some critical technologies are planned to study by the following methods. Firstly seeding tray images sequence are acquired on line, then image mosaic algorithm is applied to form a complete nursery tray sowing image, which retain the detail information of seeding tray image. Secondly estimation of the nursery tray sowing quantity per cell is achieved and sowing performance parameters are counted. According to the specific information of changes on sowing performance parameters, corresponding feedback signal is formed. In the aspect of rice seed counting algorithm, particles quantity detection is base on seed connected regions pattern recognition, multi-feature extraction and feature selection technologies. The method improves the counting accuracy of multiple particle seed quantity, and works well when seeds are overlapped, crossed and adhered. Thirdly the SIFT algorithm is applied to extract local features of seed connected regions in this project. At last the development of machine vision system ensures high-speed and efficient operation of sowing performance measurement system. The theory and method of this research will open up a new technology of precision constant seeding; also the research has great theoretical value and practical application significance.

英文关键词： Precision planter;Super hybrid rice;Machine vision;Sowing quantity;Panoramic technology