摘要
叶子是植物的重要器官，是建立植物生长模型的一个重要的组成部分。植物叶面积的检测对于评估作物的长势和建立植物的生长模型有着非常重要的研究意义。文中提出了一种可行的绿色作物叶面积检测算法，主要内容包括三部分：绿色作物图像的处理过程介绍，主要涉及的内容包括绿色提取、二值化处理和滤波去噪等；绿色作物叶面积的计算过程介绍，主要涉及的内容包括摄像头的标定、单位像素面积的计算、目标像素点的统计以及绿色覆盖区域面积的计算；叶面积检测算法效果的验证。实验结果表明：该算法的叶面积检测的误差范围在0．20％～1．29％之间，平均检测误差为0．84％。可以看出，文中提出的绿色作物叶面积检测算法具有较高的可行性。
Leaf is a vital organ of the plants to survive and it is one of the important parts in building a plant growth model. Detecting green crop leaf area plays an important role in the establishment of the plant growth model and the assessment of the plant growth state. A kind of efficient detection algorithm of green crop leaf area is put forward and the content mainly includes three parts. Firstly,it intro- duces the process of green crop pictures which involves green extraction, binarization processing and filtering denoising. Secondly,it dis- cusses the calculation process of green crop leaf area including camera calibration, unit pixel area calculation and target pixels statistics. At Last,the result of algoritb.m is verfied. The expefimeut shows that the error of the Leaf area detection ranges from 0.20% to 1. 29% and the average error is 0.84%. It can be seen that the algorithm proposed in this paper has a high feasibility. Key words： green crop; green extraction; filtering denoising ;leaf area detection ;image processing
出处
《计算机技术与发展》
2016年第8期174-176,181,共4页
Computer Technology and Development
基金
国家自然科学基金资助项目(31160253
31360289)
关键词
绿色作物
绿色提取
滤波去噪
叶面积检测
图像处理
green crop
green extraction
filtering denoising
leaf area detection
image processing
