Multi-Threshold Image Segmentation Based on Improved Bee Foraging Algorithm
The intelligent searching mechanism of bee colony for honey sources in the bee foraging algorithm is utilized to promote the optimal threshold searching efficiency of multi-threshold image segmentation,which aimed to solve the problem of low optimal threshold search efficiency for the traditional multi-threshold image segmentation methods.An adaptive neighbourhood shrinking strategy is introduced for overcoming the bee fora-ging algorithm falling into local optimum caused by a rapidly shrinking neighbourhood,where the neighbour-hood shrinking rate can be adjusted dynamically according to the stagnation state of the searching process.The strategy ensures the searching efficiency of the algorithm and further improves the optimization accuracy of the algorithm.The simulation experimental results show that the proposed method improves the optimization per-formance and robustness of the bee foraging algorithm.The experiment of multi-threshold image segmentation based on maximum inter-class variance method verifies the effectiveness of the proposed method.
万方数据
维普
