中文说明：应用背景将蚁群算法应用于图像分割领域, 提出了一种新的基于蚁群算法的图像边缘检测方法。详细阐述了蚁群算法与 该方法的基本原理和具体实现过程。为了提高算法效率, 进行两处改进, 第一将蚂蚁初始位置由随机放置修改为放置在图像边缘附近, 可取一图像灰度梯度阈值来实现, 第二将信息激素强度和启发式引导函数值均定义为像素点灰度梯度值的函数。实验结果证明了该算法能有效地检测出图像边缘, 而且具有适应性强、效率高等特点。 关关键技术蚁群算法应用于边缘检测的原理是将图像抽象成一无向图, 然后将一群蚂蚁随机放置到图中, 各个蚂蚁将根据顶点信息激素强度和启发式引导函数求得的概率从其8 邻域顶点中选择一个作为下一步的目的位置, 通过多次循环迭代最终使大多数蚂蚁聚集到图像边缘上。
English Description：
Application backgroundApplying the ant colony algorithm to the image segmentation, a new image edge detection method based on ant colony algorithm is proposed.. The ant colony algorithm and itsThe basic principle and Realization of the method. In order to improve the efficiency of the algorithm, two improvement, the first will ants initial position by randomly placed to modify is placed near the edge of the image, desirable image gray level gradient threshold to achieve, the second pheromone strength and heuristic guidance function values are defined value for the pixel gray level gradient function. Experimental results show that the proposed algorithm can detect the edge of the image effectively, and has the features of strong adaptability and high efficiency..OffKey TechnologyAnt colony algorithm is applied to the principle of edge detection is image is abstracted as a directed graph, and then a group of ants randomly placed in the graph, ea