蚁群聚类算法在隐写分析中的应用

摘要

为解决隐写分析中富模型的特征维数较高、冗余较大、不便于高效分类的问题，提出了一种基于蚁群聚类算法的降维方法。首先利用蚁群聚类算法求解特征簇的簇中心，然后把簇中心作为新的特征，提取新特征的有效部分用集成特征进行分类。实验结果表明，利用蚁群聚类算法对高维特征进行降维，可以有效去除冗余特征，提升特征的分类效果。%This paper proposed a means of dimension reduction which was based on ant colony clustering algorithm to solve the problem of steganlysis that the features had higher dimension and bigger redundancy in rich model ,which was not convenient to classify efficiently.First,this method collected the cluster center from the features of the cluster by ant colony clustering al-gorithm,Then,it regarded the cluster center as a new feature to extract the effective part from the new features and used the ensemble classifier to make classification.It turns out that reduce dimension with ant colony clustering algorithm can remove some redundant features effectively and improve the effect of features.