Based on DCIWPSO in application of valley-edge detection froth image segmentation
基于DCIWPSO在谷底边缘泡沫图像分割的应用*

In the process of mineral flotation, in order to predict the mineral grade, it needs to extract a large number of bubble image feature parameters, where bubble size is very important image characteristic parameter. Image segmentation is image processing technology that divides a bubble image into several bubble areas. The valley-edge detection segmentation algorithm is an important segmentation algorithm, which segmentation threshold is very important parameter. For standard particle swarm algorithm to calculate the threshold easily trapped into local optimal value, it is difficult to calculate the global optimum value, this paper improved particle swarm optimization, dynamic change value of the inertia weight in particle swarm optimization to achieve to be suitable for the edge split threshold, correctly achieve the purpose of froth image segmentation.