A Segmentation Method Based on Clustering Pre-segmentation and High-low Scale Distance Reconstruction for Colour Froth Image
基于聚类预分割和高低精度距离重构的彩色浮选泡沫图像分割

Due to a large variation in the quality of froth images of ore and inhomogeneity of size, shape and grayscale of bubbles, a new segmentation method based on clustering pre-segmentation and high-low scale distance reconstruction is proposed for froth images. Firstly, the segmentation between foreground froth and background mineral slurry image is achieved by the k-means clustering method and the noises are filtered according to intensity distribution and shape distribution information, and a new reconstruction combined with high-low scale distance transformation based on morphological reconstruction is presented and applied to the froth distance- transformation image. Then the precise region makers for watershed transformation are extracted by area-reconstruction h-dome improved transformation. Finally, the watershed algorithm is used to get waterline for every bubble. Bubble physical characteristics such as the bubble number and bubble size can be obtained from the segmented image,which provide the guidance for flotation control process. The experimental results show its effectiveness.