基于改进人工鱼群算法的图像边缘检测①

提出了一种基于带混沌差分进化变异算子的人工鱼群算法的图像边缘检测方法,该算法通过灰度图像矩阵的一阶导数得到灰度图像的梯度值矩阵,然后利用人工鱼群搜索图像梯度最大值,达到快速、准确检测图像边缘的目的。在差分变异算子中引入调节因子加强搜索能力,并且动态调整人工鱼的视野,使鱼群能快速跳出局部极值。通过仿真实验表明,该算法用于图像边缘检测是可行的和有效的。

Image Edge Detection Based on Improved Artificial Fish-School Swarm Algorithm

A method of image edge detection based on artificial fish swarm algorithm(AFSA)with chaos differential evolution algorithm(CDEA) is proposed in this paper. The method gets gradient matrix of grayscale image by first-order derivative, and search the maximum of image gradient with artificial fish. The detecting image edge could be achieved rapidly and accurately. The ability of search can be improved with adjustment factor in CDEA. It dynamically adjusts the vision, makes the fish jump out of the local extreme. The simulation shows that the proposed algorithm is feasible and effective.