A novel image segmentation method based on an improved bacterial foraging optimization algorithm

作者：Zeng Zhi Gao; Guan Liang Hua; Zhu Yan Hui; Liu Qiang; He Jin Rong

来源：Journal of Information Hiding and Multimedia Signal Processing, 2017, 8(2): 348-357.

• Bacterial foraging optimization
• Bacterial foraging optimization algorithms
• Bionic optimization
• Fixed step sizes
• Gray histogram
• Local searching
• Segmentation methods
• Segmentation results

When some bionic optimization algorithms are used for image segmentation, we find that the search speeds of these algorithms are slow and the local searching abilities of these algorithms need be improved. In order to solve these problems, this paper proposed a new image segmentation method based on the improved bacterial foraging optimization algorithm. Firstly, a dynamic step size is used to instead of the fixed step size of the chemotaxis operator, and a dynamic probability is used to instead of the fixed probability of elimination-dispersal operator. Then, the gray histograms of the images are extracted for the image segmentation. Ultimately, the images are segmented using the improved bacterial foraging optimization algorithm. The image segmentation results show that the accuracy and the speed of the image segmentation based on the improved bacterial foraging optimization algorithm are superior to the ones that based on others traditional bionic optimization algorithms.

• 出版日期2017