|
|||||
|
|
| 基于机器视觉的超级稻秧盘育秧播种空穴检测技术 | |
| 引用本文： | 齐 龙,马 旭,周海波.基于机器视觉的超级稻秧盘育秧播种空穴检测技术[J].农业工程学报,2009,25(2):121-125. |
| 作者姓名： | 齐 龙 马 旭 周海波 |
| 作者单位： | 1. 吉林大学生物与农业工程学院,长春,130025 2. 华南农业大学南方农业机械与装备关键技术省部共建教育部重点实验室,广州,510642 3. 佳木斯大学机械工程学院,佳木斯,154007 |
| 基金项目： | 国家自然科学基金资助项目（50775078）；国家“十一五”科技支撑计划项目（2006BAD28B01）；广东省高等学校人才引进科研资助项目；黑龙江省自然科学基金资助项目（E200841） |
| 摘 要： | 针对超级稻育秧播种量少，易出现空穴而影响产量的问题，对超级稻高速连续秧盘育秧播种的空穴进行了在线检测。在秧盘育秧流水线的播种和覆表土工序之间加入检测系统，CCD摄像机不断地拍摄穴盘图像，并建立与穴孔相对应的掩模图像，利用定时读取程序，读取缓存中的图像信息。通过图像处理和分析，有效地识别了穴盘空穴，将检测结果以电子表格的形式存储在穴盘空穴数据库中，以供人工补种，进一步降低了秧盘育秧空穴率，提高了超级稻精准育秧的成秧率。 |
| 关 键 词： | 机器视觉 图像处理 CCD摄像机 空穴检测 精密播种 秧盘育秧 超级稻 |
| 收稿时间： | 7/9/2008 12:00:00 AM |
| 修稿时间： | 2008/12/16 0:00:00 |
Seeding cavity detection in tray nursing seedlings of super rice based on computer vision technology |
|
| Qi Long,Ma Xu and Zhou Haibo.Seeding cavity detection in tray nursing seedlings of super rice based on computer vision technology[J].Transactions of the Chinese Society of Agricultural Engineering,2009,25(2):121-125. | |
| Authors: | Qi Long Ma Xu and Zhou Haibo |
| Institution: | 1. College of Biological and Agricultural Engineering, Jilin University, Changchun Jilin 130025, China,2. Key Laboratory of Key Technology on Agricultural Machine and Equipment (South China Agricultural University); Ministry of Education, Guangzhou 510642, China and 3. College of Mechanical Engineering, Jiamusi University, Jiamusi 154007, China |
| Abstract: | There are the seeding cavities due to the low seeding number of super rice, which have influence on yield in rice. For solving the problem, seeding cavities of the super rice nursing tray were detected in continuous seeding process. The vision detection procedure was arranged between seeding and covering soil in rice seeding pipeline. The CCD(Charge Coupled Device) camera shot tray images continuously, and mask images were obtained which were consistent with the tray seeding cavities. The image information of storage buffer was achieved by reading program at certain time intervals. After the images were processed and analyzed, the position of seeding cavities were tracked and results were stored in seeding cavities database for re-seeding. The technology decreased cavities ratio of tray nursing seedlings and improved the seedling survival rate of super rice precision seeding. |
| Keywords: | computer vision image processing CCD cameras seeding cavity detection precision seeding tray nursing seedlings super rice |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ | |
| 点击此处可从《农业工程学报》浏览原始摘要信息 | |
| 点击此处可从《农业工程学报》下载免费的PDF全文 | |