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Thread: Video Forensics; Pattern recognition and extrapolation

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    Video Forensics; Pattern recognition and extrapolation




    I'll just start from the beginning.

    The police edited an arrest video and the regional FBI office is acting like they can't prove it. Wish I was kidding, but I'm not.

    I know the video was edited, I was there and there are portions of conversation missing.

    There is an anomaly that indicates there was an edit, there is a breach in the pattern of flashing from the officer's squad car lights that can be seen in the reflection on the chrome bumper of the vehicle being stopped.

    I have to show this objectively, rather than "its right there can't you see it?"

    I have used VirtualDub to extract the image sequence from the .avi video and store each frame as a bitmap image.
    (60,000+ frames taking up about 58GB of space)

    I used ImageJ to convert each frame (bitmap image file) to a text file that has the Red, Green, and Blue pixel information for each pixel coordinate.
    (~16 hours of crunching to create 360GB of text files)

    I used a PERL script to extract only the information from pixel (390,379) from each frame's RGB tuple set created by ImageJ, because this is where the flashing can be seen.

    Here is where I need help.

    What is the pattern in "Blue pixel pattern before edit.txt"
    -from this pattern, extrapolate what the next 40 values should be.
    Compare extrapolated values to the values in "Blue pixel pattern during edit.txt"
    -how far off are the actual 40 frames from the extrapolated 40 frames?

    I have R, Weka, and soon may have MATLAB tools to work with.

    I took statistics way back in 2000 and no longer have my notes. I know statistics is the science I need to be working with now.

    Thank you in advance for your time.
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