基于EM和K-means混合聚类方法的植物叶片病害区域自动提取

Automatic extraction of plant diseases based on EM and K-means hybrid clustering

针对植物病害区域如何准确提取的问题,文中提出了一种基于EM和K-means混合聚类的方法。该方法在目标与背景具有较明显差异的情况下,可以有效地将叶片目标提取出来,并对较复杂背景也具有一定的甄别效果,优于其他经典方法。利用植物病害区域的褪绿特点,用K-means方法结合Lab颜色空间,利用Lab颜色空间颜色分布的均匀性,提取A分量作为参考分量,将病害区域从叶片目标中提取出来。通过Matlab仿真实验,结果表明,基于EM和K-means混合聚类方法的植物病害区域提取是可行的。

Aiming at the problem of how to extract the plant disease area accurately,a method based on EM and Kmeans hybrid clustering is proposed.The method can effectively extract the leaf target and have some screening effect on the more complicated background,which is superior to other classical methods in the case of obvious difference between the target and the background.Based on the chlorotic characteristics of the plant disease area,the K-means method was used to combine the Lab color space.Using the uniformity of the color distribution of the Lab color space,the A component was extracted as the reference component,and the disease area was extracted from the leaf target.The experimental results showed that the extraction of plant diseases based on EM and K-means hybrid clustering method is feasible.