摘要
针对当前秸秆覆盖率自动识别准确率低的问题,提出了一种更加准确,适应性更强的秸秆覆盖率检测方法。首先,基于彩色分量空间距离灰度化算法对摄像头采集的秸秆图像进行目标背景分离;其次,再将彩色图像灰度化;最后,使用基于改进的Bernsen算法对图像进行二值化处理并计算秸秆覆盖率。在实验中,选取了秸秆覆盖率区间在20%~30%、30%~40%、40%~50%、50%~60%、60%~70%、70%~80%和80%~90%各200张图片,采用改进前和改进后的Bernsen算法分别计算秸秆覆盖率,结果表明秸秆覆盖率为30%~80%时,采用改进后的Bernsen算法计算秸秆覆盖率更为准确,误差小于5%,而在其他情况下,秸秆覆盖率计算误差在5%~10%。
Aiming at the problem of low accuracy of straw coverage automatic recognition,it is proposed that a more accurate and adaptive method is used to detect straw coverage rate.Firstly,based on the color component spatial distance graying algorithm,the object and background of straw image collected by camera are separated;Secondly,the color image is grayed;Lastly,the straw image is binarized by improved Bernsen algorithm,and the straw coverage rate is calculated.In the experiment,200 pictures of straw coverage are selected with coverage range of 20%~30%,30%~40%,40%~50%,50%~60%,60%~70%,70%~80%and 80%~90%respectively.The straw coverage rate is calculated respectively by the improved Bernsen algorithm and unimproved Bernsen algorithm.The result shows that the improved Bernsen algorithm is more accurate when the straw coverage is between 30%and 80%,and the error is less than 5%.In other cases,the calculation error of straw coverage rate is between 5%and 10%.
作者
杨光
丁博
宋昕
Yang Guang;Ding Bo;Song Xin(School of Electronic Information Engineering,Changchun University of Science and Technology,Changchun 130022,China)
出处
《电子测量与仪器学报》
CSCD
北大核心
2021年第12期158-166,共9页
Journal of Electronic Measurement and Instrumentation
基金
吉林省教育厅科学计划(JJKH20190545KJ,JJKH20200778KJ)
吉林省科技厅科学计划(20180201090GX)项目资助。
关键词
秸秆覆盖率
灰度化
图像处理
二值化算法
straw coverage
graying
image processing
binarization algorithm