Remove Background using OpenCV in C++ - image

Question

Sorry for lengthier explanation. As am new to Open want to give more details with example.
My requirement is to find the delta of 2 static images, for this am using the following technique:
cv::Mat prevImg = cv::imread("prev.bmp");
cv::Mat currImg = cv::imread("curr.bmp");
cv::Mat deltaImg;
cv::absdiff(prevImg,currImg,deltaImg);
cv::namedWindow("image", CV_WINDOW_NORMAL);
cv::absdiff(prevImg,currImg,deltaImg);
cv::imshow("image", deltaImg);
And in the deltaImg, am getting the difference between the images, but it includes the background of the first image also. I know i have to remove the background using BackgroundSubtractorMOG2, but am unable to understand this class usage as most of the examples are based on webcamera captures.
Please note that my images are static (Screen shots of the desktop activity).
Please guide me in resolving this issue, some sample code will be helpful.
Note I want to calculate delta in RGB.
Detailed Explination:
Images are at : https://picasaweb.google.com/105653560142316168741/OpenCV?authkey=Gv1sRgCLesjvLEjNXzZg#
Prev.bmp: The previous screen shot of my dektop
curr.bmp: The current screen shot of my desktop
The delta between the prev.bmp and curr.bmp, should be the startup menu image only, please find the image below:
The delta image should contain only the startup menu, but even contains the background image of the prev.bmp, this background i want to remove.
Thanks in advance.

Answer 1

After computing cv::absdiff your image contains non-zero values for each pixel that changed it's value. So you want to use all image regions that changed.
cv::Mat deltaImg;
cv::absdiff(currImg,prevImg,deltaImg);
cv::Mat grayscale;
cv::cvtColor(deltaImg, grayscale, CV_BGR2GRAY);
// create a mask that includes all pixel that changed their value
cv::Mat mask = grayscale>0;
cv::Mat output;
currImg.copyTo(output,mask);
Here are sample images:
previous:
current:
mask:
output:
and here is an additional image for the deltaImg before computing the mask:
Problems occur if foreground pixels have the same value as background pixel but belong to some other 'objects'. You can use cv::dilate operator (followed by cv::erode) to fill single pixel gaps. Or you might want to extract the rectangle of the start menu if you are not interested in all the other parts of the image that changed, too.