A NOVEL STEGANALYSIS OF LSB MATCHING BASED ON KERNEL FDA IN GRAYSCALE IMAGES

被引：0
|
作者：
Hu, Lingna [1 ]
Jiang, Lingge [1 ]
He, Chen [1 ]
机构：
[1] Shanghai Jiao Tong Univ, Dept EE, Shanghai 200240, Peoples R China
来源：
2008 INTERNATIONAL CONFERENCE ON NEURAL NETWORKS AND SIGNAL PROCESSING, VOLS 1 AND 2 | 2007年
关键词：
blind detection; LSB steganalysis; image segmentation; local image complexity; Kernel FDA;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
To detect presence of LSB matching blindly, a novel steganalysis is proposed. First, image segmentation is employed to separate image into different domains. Second, statistic property of node degree for minimum spanning tree (MST) in random domain is analyzed. And third, local image complexity is proposed to describe concrete domain situation, and image features are also extracted accordingly. Simulation results demonstrate that the proposed algorithm can achieve higher detection probability than existent ones on both uncompressed and compressed image formats, especially low embedding rate.
引用
收藏
页码：556 / 559
页数：4
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