CAJ | 학술논문

当前主要的隐写分析方法都是对整幅图像进行特征提取，而忽略了图像的内容差异。该文提出一种基于四叉树分割的 JPEG 隐写分析方法，该方法根据图像块的纹理复杂度进行图像分割，对具有相同统计特性的子图像分别进行隐写检测特征的提取，并构造相应的分类器，通过加权融合得到最终的检测结果。实验结果表明该方法具有良好的性能，尤其是在训练与测试图像的统计特性具有较大差异时，该算法的检测准确率提高更加明显。
당전주요적은사분석방법도시대정폭도상진행특정제취，이홀략료도상적내용차이。해문제출일충기우사차수분할적 JPEG 은사분석방법，해방법근거도상괴적문리복잡도진행도상분할，대구유상동통계특성적자도상분별진행은사검측특정적제취，병구조상응적분류기，통과가권융합득도최종적검측결과。실험결과표명해방법구유량호적성능，우기시재훈련여측시도상적통계특성구유교대차이시，해산법적검측준학솔제고경가명현。
The traditional image steganalysis methods are based on the features extracted from the whole image, while ignoring the differences of the image content. A new JPEG steganalysis algorithm using quad-treebased segmentation is proposed. First, the given images are segmented to sub-images according to the texture complexity. Then, then steganalysis features of each sort of sub-images with the same or close texture complexity are extracted separately to build a classifier. Finally, the steganalysis results of the whole image are obtained by weighted fusing of all the sub-image categories. Experimental results demonstrate that the proposed algorithm exhibits excellent performance and significantly improves the detection accuracy.