一种改进分水岭算法的浮选泡沫图像分割方法

为了解决煤泥浮选泡沫图像分割中传统分水岭算法的过分割问题,提出了一种基于自适应标记提取的改进分水岭算法。该方法首先对浮选泡沫图像进行高斯滤波,再运用基于形态学的扩展最大值技术从泡沫图像中自适应提取标记,利用标记对梯度图像进行修改,最后使用分水岭算法对修正后的梯度图像进行分割。试验结果表明,改进后的算法克服了标记提取需要先验知识、分割过程繁琐等问题,使参数选取更加合理,分割结果更加准确。

An flotation froth image segmentation method utilizing improved watershed algorithm

In order to solve the over-segmentation problem in traditional watershed segmentation algorithm in slime flotation froth images,this paper proposes an improved watershed segmentation algorithm method which is based on adaptive maxima-marker extraction.Firstly,it carries on Gaussian filtering to flotation froth image,then,the markers are adaptively extracted from the bubble image by using the maximum expansion technology based on the morphology,after that the markers are used to modify the gradient image.Finally,the revised gradient image is processed with watershed segmentation algorithm.The experimental results show that improved algorithm solved some problems,for example,we must grasp a priori knowledge before extracting the markers,the segmentation process is complicated and so on,and the improved algorithm can select parameter in a more reasonable way,and get a more accurate segmentation result.