基于改进的Bernsen秸秆覆盖率图像处理算法研究

Research on image processing algorithm of straw coveragebased on improved Bernsen

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%.