How do I fix eroded rectangles?

Basically, I have an image like this

or one with multiple rectangles within the same image. The rectangles are completely black and white have "dirty" edges and gouges, but it's pretty easy to tell they're rectangles. To be more precise, they are image masks. The white regions are parts of the image which are to be "left alone", but the black parts are to be made bitonal.

My question is, how do I make a nice and crisp rectang开发者_如何转开发le out of this degraded one? I am a Python person, but I have to use Qt and C++ for this task. It would be preferable if no other libraries are used.

Thanks!

If the bounding box that contains all non-black pixels can do what you want, this should do the trick:

int boundLeft = INT_MAX;
int boundRight = -1;
int boundTop = INT_MAX;
int boundBottom = -1;
for(int y=0;y<imageHeight;++y) {
    bool hasNonMask = false;
    for(int x=0;x<imageWidth;++x) {
        if(isNotMask(x, y)) {
            hasNonMask = true;
            if(x < boundLeft) boundLeft = x;
            if(x > boundRight) boundRight = x;
        }
    }
    if(hasNonMask) {
        if(y < boundTop) boundTop = y;
        if(y > boundBottom) boundBottom = y
    }
}

If the result has negative size, then there's no non-mask pixel in the image. The code can be more optimized but I haven't had enough coffee yet. :)

Usually you'd do that by repeatedly dilating and eroding the mask. I don't think qt has premade functions for that, so you probably have to implement them yourself if you don't want to use libraries - http://ostermiller.org/dilate_and_erode.html has information on how to implement the functions.

For the moment, we'll assume they're all supposed to come out as rectangles with no rotation. In this case, you should be able to use a pretty simple approach. Starting from each pixel at the edge of the bitmap, start sampling pixels working your way inward until you encounter a transition. Record the distance from the edge for each transition (if there is one). Once you've done that from each edge, you basically "take a vote" -- the distance that occurred most often from that edge is what you treat as that edge of the rectangle. If the rectangle really is aligned, that should constitute a large majority of the distances.

If, instead you see a number of distances with nearly equal frequencies, chances are that the rectangle is rotated (or at least one edge is). In this case, you can divide the side in half (for example) and repeat. Once you've reached a large majority of points in each region agreeing on the distance, you can (attempt to) linearly interpolate between them to give a straight line (and limiting the minimum region size will limit the maximum rotation -- if you get to some size without reaching agreement, you're looking at a gouge, not the rectangle edge). Likewise, if you have a region (or more than one) that doesn't fit cleanly with the rest and won't fit with a line, you should probably ignore it as well -- again, you're probably looking at a gouge, not what's intended as an edge.