改进的细菌觅食算法在图像分割中的应用

Application of an Improved Bacterial Foraging Algorithm to Image Segmentation

针对一些仿生算法应用于图像分割时其搜索速度缓慢,易陷入局部最优等问题,提出一种改进的细菌觅食算法,并将其应用到图像分割领域。首先,把传统细菌觅食算法的趋化算子的固定步长替换为动态步长,把其迁徙算子的固定迁徙概率替换为动态迁徙概率;然后,利用图像的灰度直方图作为特征,并使用改进的细菌觅食算法进行图像分割。实验结果表明,使用基于改进细菌觅食算法的图像分割方法,在准确率和速度方面都优于其他传统仿生算法。

In view of the slow search speed and high frequency of local optimum resulting from the application of some bionic algorithms to the image segmentation,an improved bacterial foraging algorithm has been proposed for this specific purpose.Firstly,in the traditional bacterial foraging algorithm,chemotaxis operators,fixed step size is to be replaced with dynamic step size,and migration operators,fixed migration probability is to be replaced with dynamic migration probability.Then,the gray histograms of the images are to be extracted for the image segmentation,followed by an image segmentation by adopting the improved bacterial foraging optimization algorithm.The experimental results show that the accuracy and the speed of the image segmentation based on the improved bacterial foraging optimization algorithm are superior to those that are based on other conventional bionic algorithms.