基于蚁群的自适应边缘检测

2013 8th International Workshop on Systems, Signal Processing and their Applications (WoSSPA) Pub Date : 2013-05-01 DOI:10.1109/WOSSPA.2013.6602361

K. Benhamza, H. Merabti, Hamid Seridi

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引用次数: 7

摘要

提出了一种基于蚁群算法的自适应边缘检测方法。蚁群算法是一种基于群的元启发式算法，其灵感来源于自然界蚁群的自组织特性。运动中的人工蚂蚁会生成一个信息素图，该信息素图表示边缘图像的数据。进一步的行为被添加到每只蚂蚁对局部刺激的反应中:蚂蚁可以自我繁殖并引导其祖先向适当的方向发展，以加强在适当领域的研究，如果超过特定的年龄，它也可以死亡，从而消除无效的搜索。实验结果表明，该技术的性能丰富了这些行为。该算法对各种图像的边缘提取具有良好的分割效果，提取速度快，适应性强。

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Adaptive edge detection using ant colony

In this paper, an adaptive edges detection method based on ant colony algorithm is presented. Ant colony algorithm is a swarm-based metaheuristic inspired by the self-organizing properties of ant colony in nature. Artificial ants in movement create a pheromone graph, which denotes data of edge image. Further behaviors were added to each ant in response to local stimuli: the ant can self-reproduce and lead its progenitors in an appropriate direction to enhance research in suitable areas and it can die too if it exceeds a specific age and so eliminate the ineffective search. Experimental results show the performance of this technique enriched with these behaviors. It provides a good segmentation, fast and adaptive in extracting edges for a variety of images.

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来源期刊

2013 8th International Workshop on Systems, Signal Processing and their Applications (WoSSPA)

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