Re: Image Analysis

Maybe you could simply force the images to black and white, then count the number of black pixels in each image - images with more black pixels have foreign matter?

For a more complex case, that may be too simple, but generating a histogram based on pixel color might be one way to map each image into some form of numerical data for further comparison.

Comment on Re: Image Analysis

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Re^2: Image Analysis by fluffyvoidwarrior (Monk) on Oct 25, 2010 at 15:37 UTC
Yes I'd considered that approach. The trouble is that the level of background noise can vary quite considerabley (but gradually). So I considered keeping a running average of quiescent noise and comparing each sample frame to this variable baseline. Instant changes are a good indicator. Currently I'm thinking along the lines of a spam filter with several tests returning a score and when they add up to a given threshold level it is considered a "hit". The occasional false positive isn't a problem but operators will simply ignore a frequent false warning alarm	[reply]

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Re^2: Image Analysis
by fluffyvoidwarrior (Monk) on Oct 25, 2010 at 15:37 UTC

Yes I'd considered that approach. The trouble is that the level of background noise can vary quite considerabley (but gradually). So I considered keeping a running average of quiescent noise and comparing each sample frame to this variable baseline. Instant changes are a good indicator. Currently I'm thinking along the lines of a spam filter with several tests returning a score and when they add up to a given threshold level it is considered a "hit". The occasional false positive isn't a problem but operators will simply ignore a frequent false warning alarm

[reply]