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Image content analysis for sector-wise JPEG fragment classification

机译:图像内容分析,按扇区进行JPEG片段分类

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摘要

In this paper, we propose a sector-wise JPEG fragment classification approach to classify normal and erroneous JPEG data fragments with the minimum size of 512 bytes per fragment. Our method is based on processing each read-in sector of 512 bytes with using the DCT coefficient analysis methods for extracting the features of visual inconsistencies. The classification is conducted before the inverse DCT and can be performed simultaneously with JPEG decoding. The contributions of this work are two-folds: (1) a sector-wise JPEG erroneous fragment classification approach is proposed (2) new DCT coefficient analysis methods are introduced for image content analysis. Testing results on a variety of erroneous fragmented and normal JPEG files prove the strength of this operator for the purpose of forensics analysis, data recovery and abnormal fragment inconsistencies classification and detection. Furthermore, the results also show that the proposed DCT coefficient analysis methods are efficient and practical in terms of classification accuracy. In our experiment, the proposed approach yields a false positive rate of 0.32% and a true positive rate of 96.1% in terms of erroneous JPEG fragment classification.
机译:在本文中,我们提出了一种按扇区划分的JPEG片段分类方法,以对正常和错误的JPEG数据片段进行分类,每个片段的最小大小为512字节。我们的方法基于使用DCT系数分析方法处理512字节的每个读入扇区,以提取视觉不一致的特征。分类是在逆DCT之前进行的,可以与JPEG解码同时进行。这项工作的贡献有两个方面:(1)提出了一种基于扇区的JPEG错误片段分类方法(2)引入了新的DCT系数分析方法来进行图像内容分析。在各种错误的碎片和正常JPEG文件上的测试结果证明了该操作员的实力,可以进行法医分析,数据恢复以及异常碎片不一致的分类和检测。此外,结果还表明,所提出的DCT系数分析方法在分类精度方面是有效和实用的。在我们的实验中,根据错误的JPEG片段分类,所提出的方法产生的假阳性率为0.32%,真正的阳性率为96.1%。

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