PROJECT TITLE :

A Deterministic Approach to Detect Median Filtering in 1D Data

ABSTRACT:

During this paper, we have a tendency to propose a forensic technique that is in a position to detect the appliance of a median filter to 1D information. The strategy depends on deterministic mathematical properties of the median filter, which result in the identification of specific relationships among the sample values that can't be found within the filtered sequences. Hence, their presence within the analyzed 1D sequence permits excluding the appliance of the median filter. Because of its deterministic nature, the method ensures zerop.c false negatives, and though false positives (sequences not filtered classified as filtered) are theoretically potential, experimental results show that the false alarm rate is null for sufficiently long sequences. Furthermore, the proposed technique has the aptitude to locate with good precision a median filtered half of 1-D data and provides a sensible estimate of the window size used.


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