摘要
为了远程实时动态监测玉米长势,为农事活动提供准确的玉米生长状态信息,提出了基于轮廓和骨架提取的玉米出苗期和三叶期的自动识别算法。该算法实现了对玉米图像的分割,并对图像中轮廓和骨架等图像特征进行提取,根据所提取的图像特征判断玉米是否进入出苗期或三叶期。利用该算法与计算机视觉库openCV进行玉米出苗期和三叶期的检测系统的设计,实现了玉米出苗期和三叶期的自动识别。此外,在VS2013环境下实现了对一个简单的玉米出苗期和三叶期的自动检测系统软件的界面开发。该系统对玉米出苗期和三叶期的识别速度较快,识别结果准确,可以作为玉米全部生长期检测系统的开发基础。
The automatic recognition algorithm of emergence and three-leaf stage of maize is proposed in order to dynamically monitor the growth of maize in real-time and provide accurate information about growth status for farming activities. This algorithm realizes segmentation of corn images and extract image characteristics such as contour and skeleton. To determine whether the corn has been in emergence and three-leaf stage according to the extracted image features. This algorithm and computer vision class library openCV are used for the design of emergence and three-leaf stage detection system and the target of detecting emergence and three-leaf stage of maize is achieved automatically. What＇ s more, in the environment of VS2013, it achieved the development of this detection system. The speed of this detection system is fast and the test results are accurate. It can be used as the development foundation of all maize growth period detection system.
出处
《电子测量与仪器学报》
CSCD
北大核心
2017年第10期1574-1581,共8页
Journal of Electronic Measurement and Instrumentation
基金
国家自然科学基金(61671248)
江苏省产学研联合创新资金计划(BY2013007-02)
江苏省高校自然科学研究重大项目(15KJA460008)
江苏省"六大人才高峰"计划
江苏省"信息与通信工程"优势学科资助
