Counter Image Forensics Essay

3278 Words Jan 28th, 2015 14 Pages
Chapter 3 IMPLEMETATION

3.1. JPEG COMPRESSION USING MATLAB 7.10.0

3.1.1 Workflow

We successfully compressed a black & white photograph (source: Dresden Image Database) implementing JPEG algorithm in Matlab and compressed the images to 1/4th of the original image size. This was achieved by dividing the image in blocks of 8×8 pixels and applying a discrete cosine transform (DCT) on each partition of the images. The resulting coefficients were quantized and less significant coefficients are set to zero. In order to omit redundancy in our algorithm, we skipped the entropy encoding step, since it provides lossless compression and thus not useful for forensic of the image. This is shown in figure 3.1.

3.1.2 Block splitting
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Using this quantization matrix with the DCT coefficient matrix from above resulted in:

Figure 3.2: Unquantized DCT coefficients

Figure 3.3: Quantized DCT coefficients

3.1.4 Decompression

As mention before, we skipped entropy encoding step, since it do not produce any finger print which can be used to develop a forensic technique. Thus, above mentioned were followed in bottom to up direction. An original image and its compressed version is shown in Fig.3.4 and Fig.3.5, respectively.

Figure 3.4 Comparison between (a) Original Image and (b) Image after implementing JPEG Compression with Quality factor of 50

3.2 ANTI FORENSIC FRAMEWORK TO HIDE JPEG COMPRESSION FINGERPRINTS

We have implemented the algorithm proposed by J. He, Z. Lin, L.Wang, and X. Tang in their research paper “Detecting doctored JPEG images via DCT coefficient analysis” to counter the forensic technique which uses localized evidence of double JPEG compression to identify image forgeries.

3.2.1 Framework
JPEG is a lossy image compression techniques which operate by applying a two-dimensional invertible transform, such as the DCT to an image as a whole, or to each set of pixels within an image that

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