Noise removal to create mask in OpenCV

Question

I need to create a mask to retrieve an object (foreground object) based on two related images.

Image 1:

[![enter image description here]

Image 2:

[![enter image description here]

The images contain a foreground object and a background with texture. The two images are mostly the same except that in image2, the foreground object may have changed a little bit (it could have been rotated, translated or/and scaled).

Using OpenCV, I did the followings:

• perform image alignment (using findTransformECC with param cv::MOTION_AFFINE) to get transformation of foreground;
• do transformation to image1 (using cv::warpAffine with param cv::INTER_LINEAR + cv::WARP_INVERSE_MAP) based on the transform matrix above;
• do absolute diff (cv::absdiff & cv::threshold with param cv::THRESH_BINARY_INV) between image2 and already transformed image1.

I think I am close to my goal but I still can not get clean mask of foreground object due to remaining noises on the background area.

What is the solution to remove all noise on the image_absdiff_invert.png (above) in order to create a clean mask of the foreground object ?

Answer 1

I just tried it.

Using morphological operations is often a bit tricky (trial and error) and gives me this result:

While using a median filter might be a good pre-processing (or maybe even enough for your contour extraction) and gives this result (this is just median blur from the input image, no morphological operations yet):

here's the test code:

int main(int argc, char* argv[])
{
    cv::Mat input = cv::imread("C:/StackOverflow/Input/maskNoise.png", CV_LOAD_IMAGE_GRAYSCALE);

    cv::Mat mask = input.clone();

    cv::dilate(mask, mask, cv::Mat());
    cv::dilate(mask, mask, cv::Mat());
    cv::erode(mask, mask, cv::Mat());
    cv::erode(mask, mask, cv::Mat());

    cv::erode(mask, mask, cv::Mat());
    cv::erode(mask, mask, cv::Mat());
    //cv::erode(mask, mask, cv::Mat());
    //cv::erode(mask, mask, cv::Mat());
    //cv::dilate(mask, mask, cv::Mat());
    //cv::dilate(mask, mask, cv::Mat());
    cv::dilate(mask, mask, cv::Mat());
    cv::dilate(mask, mask, cv::Mat());

    cv::Mat median;
    cv::medianBlur(input, median, 7);

    cv::Mat resizedIn;
    cv::Mat resizedMask;
    cv::Mat resizedMedian;
    cv::resize(mask, resizedMask, cv::Size(), 0.5, 0.5);
    cv::resize(median, resizedMedian, cv::Size(), 0.5, 0.5);
    cv::resize(input, resizedIn, cv::Size(), 0.5, 0.5);

    cv::imshow("input", resizedIn);
    cv::imshow("mask", resizedMask);
    cv::imshow("median", resizedMedian);

    cv::imwrite("C:/StackOverflow/Output/maskNoiseMorph.png", mask);
    cv::imwrite("C:/StackOverflow/Output/maskNoiseMedian.png", median);
    cv::waitKey(0);
    return 0;
}