We implement AntClust, a clustering algorithm based on the chemical recognition system of ants and use it to cluster images of cars. We will give a short recap summary of the main working principles of the algorithm as devised by the original paper [1]. Further, we will describe how to define a similarity function for images and how the implementation is used to cluster images of cars from the vehicle re-identification data set. We then test the clustering performance of AntClust against DBSCAN, HDBSCAN and OPTICS. Finally one of the core parts in AntClust, the rule set can be easily redefined with our implementation, enabling a way for other bio-inspired algorithms to find rules in an automated process. The implementation can be found on GitLab [9].

翻译：本文实现了基于蚂蚁化学识别系统的聚类算法AntClust，并将其应用于汽车图像聚类。首先简要回顾了原始论文[1]所提出的算法核心工作原理。随后阐述了图像相似度函数的定义方法，以及如何利用该实现方案对车辆重识别数据集中的汽车图像进行聚类。接着将AntClust与DBSCAN、HDBSCAN和OPTICS算法进行了聚类性能对比测试。最后指出，通过本实现可便捷地重新定义AntClust的核心模块——规则集，为其他仿生算法在自动化过程中寻找规则提供了可行方案。该实现代码已发布于GitLab[9]。