%0 Journal Article %T Detection of stego images using one-class support vector machines with multiple hyperspheres
多超球面OC-SVM算法在隐秘图像检测中的应用 %A TANG Yu-hua %A YANG Xiao-yuan %A ZHANG Min-qing %A HAN Peng %A
唐玉华 %A 杨晓元 %A 张敏情 %A 韩鹏 %J 计算机应用 %D 2006 %I %X In order to reduce the complexity and weak generalization of classification method using two class support vector machines in images steganalysis, a new Kernel-based classification method using OC-SVMs with multiple hyperspheres was put forward. Considering that the data features were expected to be more separable in kernel space, we first performed the K-means clustering in kernel space, then trained the sub-class data separately using OC-SVMs and established a multiple hyperspheres classification model to decide the class label of new data. The experimental results show that this method has efficiently improved the classification precision. %K blind detection %K images steganalysis %K Kernel-based K-means clustering %K multiple hypersphere %K One-Class Support Vector Machines (OC-SVM)
盲检测 %K 图像密写分析 %K 核K-均值聚类 %K 多超球面 %K 一类支持向量机 %U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=831E194C147C78FAAFCC50BC7ADD1732&aid=3DB3EA5EC1F4C169&yid=37904DC365DD7266&vid=96C778EE049EE47D&iid=59906B3B2830C2C5&sid=E3511D325C01F2EB&eid=0A4E263351E626B4&journal_id=1001-9081&journal_name=计算机应用&referenced_num=0&reference_num=7