论文部分内容阅读
提出了一种新的基于遗传算法和支持向量机的隐藏图像检测方法。用遗传算法进行图像特征选择,采用支持向量机作为分类器,将支持向量机的分类效果作为适应度函数值返回,指导遗传算法搜索最优的特征,移除图像的不相关特征和冗余特征,提高了学习效率。实验结果表明,与仅采用支持向量机分类但未进行特征选择的隐藏检测方法相比,本方法能有效地提升分类器性能。
A new hidden image detection method based on genetic algorithm and support vector machine is proposed. The genetic algorithm is used to select the image features. The support vector machine is used as the classifier, and the classification effect of the SVM is returned as the fitness function value, which guides the genetic algorithm to search for the optimal features and removes the irrelevant and redundant features of the images , Improve learning efficiency. The experimental results show that the proposed method can effectively improve the performance of the classifier compared with the hidden detection method which only uses the support vector machine but has no feature selection.