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    <p>General background subtraction is an unsolved problem, so getting perfect results is going to be a big effort. With that said, you can probably get close. Here are a couple of suggested avenues:</p> <ol> <li><p>I am guessing that your app will place clothes on a human, or something of the sort. Instead of getting a perfect segmentation, run a <a href="http://lear.inrialpes.fr/people/triggs/pubs/Dalal-cvpr05.pdf" rel="noreferrer">person detector</a>, remove all of the image except for the detected person, and fit a part-based human model to the remaining image. Then you have the pose of the person, and can do your image processing accordingly.</p></li> <li><p>Allow the user to input some strokes from the foreground and some strokes from the background, and run a <a href="http://lvelho.impa.br/ip12/reading/ijcv06.pdf" rel="noreferrer">graph-cuts-based image segmentation algorithm</a> on the frame.</p></li> <li><p>Begin your process by having the user not be present in your video stream. From this, learn the background distribution (start with a simple histogram of background pixels, there are much more elaborate schemes but you need a starting place). Then, when the user enters the scene, create a binary image containing the <a href="http://en.wikipedia.org/wiki/Connected-component_labeling" rel="noreferrer">connected components</a> that don't fit into the learned background distribution. This will not be perfect, but you will start to see something close to a binary image where the white pixels are your user, and the black pixels are the background. Use <a href="http://en.wikipedia.org/wiki/Mathematical_morphology" rel="noreferrer">morphology operators</a> to join any large connected components that are slightly separated, and threshold your image to remove small noise in the image, from things like specular objects and illumination changes.</p></li> </ol> <p>Like I said (and is mentioned in the comments), this is not an easy problem, but you can come up with a good approximation if you put some time into it. I suggest the third method I listed. It is achievable, and can be broken down into small parts so you can tell when you're making progress.</p> <p>Good luck!</p>
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    1. POHow to segment an image in iOS to remove background and retain the foreground picture
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    1. COHi, Chris thank you so much for the information currently im trying to find contours in the image by defining the rect for the foreground image and converting it to gray scale and masking the background part of the image but am not sure wether im proceeding in the right way.
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