摘要
提出一种基于遗传算法和多超球面一类支持向量机的隐秘图像检测方案。为了得到最能反映分类本质的特征从而有效实现分类识别,采用遗传算法进行图像特征选择,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选择方案。实验结果表明,与仅采用支持向量机分类而未进行特征选择的隐秘检测方案相比,该方案提高了隐秘图像检测的识别率。
In order to reduce the complexity of computation and improve the generalization of two binary-class support vector machines in images steganalysis,this paper brings forward a steganalysis method based on genetic algorithms and multiple one-class SVM.Genetic algorithm is applied to search and identify the potential informative features combinations for classification.The classification accuracy from the support vector machine classifier is used to determine the fitness in genetic algorithm.Experimental results show that the efficiency of detecting system is improved.
出处
《计算机工程》
CAS
CSCD
北大核心
2008年第8期159-161,共3页
Computer Engineering
基金
国家自然科学基金资助项目(60473029)
国家部委基金资助项目
网络与信息安全教育部重点实验室课题基金资助项目(200409)
