返回
Constructing local information feature for spatial image steganalysis
DOI:10.1007/s11042-016-3751-1.png)
摘要
En 中文
Feature is a key part for steganalysis. In this paper we propose a spatial feature set for image steganalysis, named Local Information Feature (LIF), to increase the diversity of spatial steganalysis feature and improve its performance. It also provide a heuristic framework for designing steganalysis feature through 3 steps. It first collects local information from its local region consisting of adjacent pixels. Then according to certain rules, it maps each pixel to its corresponding local type by its local information. Finally, the feature set is formed by adaptive weighted statistical histograms of local types. We design two schemes for LIF, each of which can generate different feature sets using different methods of local information computing. Experimental results show that our feature is effective for detecting stego images embedded by adaptive steganography. We also discussed some possible method to extent the feature designing based on LIF.
Keyword:
Spatial image steganalysis
Local feature
Image steganography
Spatial rich model
AI总结
对已上传原文的论文进行重点信息的提取,主要内容包括:简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
3
论文数:
2.0W
被引数:
3.2W
机构
引用论文
Assessing toxicity mechanism of silver nanoparticles by using brine shrimp (Artemia salina) as model
Chemosphere
IF0
没有更多内容

