蚁群算法在图像边缘检测中的应用

Susmita Koner, S. Acharyya
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引用次数: 3

摘要

图像中的边缘是由像素组成的曲线,其中两侧包含强度不均匀的像素。边缘检测是低层图像处理的一部分,在各个领域都非常需要。虽然边缘检测可以通过各种衍生技术完成,但也可以使用元启发式近似算法很好地检测到边缘。蚁群算法(Ant Colony Optimization, ACO)就是解决这一问题的一种元启发式方法。在包括初始化、构建、更新、决策和可视化五个阶段的基本蚁群算法中,我们通过修改初始化和构建阶段,提出并实现了总共八个变化。在初始化阶段,我们在一个变体中给出了一个约束,即蚂蚁将在边缘附近初始化,以消除无用的构造步骤和不必要的边缘检测,而另一个变体没有这个约束,这可能会在生成的图像中产生不必要的边缘。我们在构建阶段选择下一个像素时采取了另外两种变化:在一种贪心方法中使用,在另一种轮盘选择方法中使用。除此之外,根据蚂蚁的内存大小,在这个阶段还做了另外两个变化,即应用蚂蚁的禁忌列表内存和没有内存的蚂蚁。因此,在采用两种选择方法、两种蚂蚁内存大小和两种初始化阶段的基础上,我们分别实现了八种变量。我们观察到,具有轮盘选择、结合蚂蚁禁忌表记忆和新初始化条件的变体优于其他变体。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Ant colony optimization variants in image edge detection
Edges in an image are the curves consisting of pixels wherein both side contains pixels with non-uniform intensity. Edge detection is a part of low level image processing, much needed in various fields. Though edge detection can be done by various derivative techniques but it can also be detected well using meta-heuristic approximation algorithms. Ant Colony Optimization (ACO) is such a meta-heuristic technique to solve it. In basic ACO which comprises five phases: Initialization, Construction, Updation, Decision and Visualization, we have proposed and implemented total eight variations in this paper by modifying initialization and construction phase. In the initialization phase we have given a constraint in one variant that ants will be initialized near to edge to eliminate useless construction steps and unwanted edge detection where the other variant is without this constraint which may generate unnecessary edges in the resulting image. We have taken other two variations in selecting the next pixel in the construction phase: in one Greedy method is used, in another Roulette wheel selection method is used. Apart from these, in this phase two more variations have been done depending on memory size of ants i.e. applying tabu list memory of ants and ants without memory. Hence on the basis of two types of selection method used, two types of memory size of ants and two types of initialization phase, we have implemented eight variations individually in this paper. We observe that the variant, with roulette wheel selection, incorporated with the tabu list memory of ants, and with the new initialization condition outperforms others.
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