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Emgu.CV, a .Net wrapper to OpenCV comes with a video surveillance example. If used with a laptop embedded camera under artificial lightning, the whole picture is “noisy”, and a foreground detected by an OpenCV’s FGDetector is massive.
What can I do (plain OpenCV answer will also work) to filer out this noise to feed a relatively nosiseless image to a BlobTracker?
If you are using a simple Background Substraction, where you just have a previous background model and substract it from the current input image to generate a binary image representing 255 – Foreground / 0 – Background, you can look for connected components within the binary image and if they don’t occupy a certain minimum area, they are filtered out (turned from 255 to 0).
Using OpenCV, you can use findContours to find all the blobs within the image and use contourArea to check if the blob is big enough to be considered a foreground.
Than you use fillPolly to fill the big blobs with 255(white) and the small blobs with 0(black).