Steganalysis versus Splicing detection Paper by: Yun Q. Shi, Chunhua Chen, Guorong Xuan and Wei Su By: Nehal Patel Siddharth Samdani. ECE643 DIGITAL IMAGE PROCESSING. Agenda.
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From the Greek word steganos meaning “covered”– and the Greek word graphie meaning “writing”
The spliced image is a composite picture generated by combining image fragments from the same or different images without further post-processing such as smoothing of boundaries among different fragments.
B,C : Original Images A : Spliced Image
Subjective measurement for steganalysis:
Objective measurement for Steganalysis:
5/6 of authentic and 5/6 of the spliced images are used to train a SVM classifier and remaining 1/6 of these images are used to test the trained classifier.
Some Universal Steganalysis methods:
Multi-size Block Discrete Cosine Transform (MBDCT)
The image is divided into nxn non overlapping blocks. Then DCT is applied independently on each block, which gives a 2-D array consisting of BDCT coefficients of all the blocks. Using individual block size corresponding BDCT 2-D array is obtained. Each of this BDCT 2-D array generates corresponding features.
Moment Based Features
Markov based features:
The implementation results of novel natural image model on image dataset :
The ROC curves of applying the natural image model