CODEWITHSUNDEEP
opencv
Anton111111
Anton111111

Reputation: 686

Can't determine document edges from camera with OpenCV

I need find edges of document that in user hands.

1) Original image from camera:

enter image description here

2) Then i convert image to BG:

enter image description here

3) Then i make blur:

enter image description here

3) Finds edges in an image using the Canny:

enter image description here

4) And use dilate :

enter image description here

As you can see on the last image the contour around the map is torn and the contour is not determined. What is my error and how to solve the problem in order to determine the outline of the document completely?

This is code how i to do it:

final Mat mat = new Mat();
    sourceMat.copyTo(mat);

    //convert the image to black and white
    Imgproc.cvtColor(mat, mat, Imgproc.COLOR_BGR2GRAY);

    //blur to enhance edge detection
    Imgproc.GaussianBlur(mat, mat, new Size(5, 5), 0);
    if (isClicked) saveImageFromMat(mat, "blur", "blur");

    //convert the image to black and white does (8 bit)
    int thresh = 128;
    Imgproc.Canny(mat, mat, thresh, thresh * 2);

    //dilate helps to connect nearby line segments
    Imgproc.dilate(mat, mat,
            Imgproc.getStructuringElement(Imgproc.MORPH_RECT, new Size(3, 3)),
            new Point(-1, -1),
            2,
            1,
            new Scalar(1));

Upvotes: 0

Views: 320

Answers (1)

Chungzuwalla
Chungzuwalla

Reputation: 1068

This answer is based on my above comment. If someone is holding the document, you cannot see the edge that is behind the user's hand. So, any method for detecting the outline of the document must be robust to some missing parts of the edge.

I suggest using a variant of the Hough transform to detect the document. The Wikipedia article about the Hough transform makes it sound quite scary (as Wikipedia often does with mathematical subjects), but don't be discouraged, actually they are not too difficult to understand or implement.

The original Hough transform detected straight lines in images. As explained in this OpenCV tutorial, any straight line in an image can be defined by 2 parameters: an angle θ and a distance r of the line from the origin. So you quantize these 2 parameters, and create a 2D array with one cell for every possible line that could be present in your image. (The finer the quantization you use, the larger the array you will need, but the more accurate the position of the found lines will be.) Initialize the array to zeros. Then, for every pixel that is part of an edge detected by Canny, you determine every line (θ,r) that the pixel could be part of, and increment the corresponding bin. After processing all pixels, you will have, for each bin, a count of how many pixels were detected on the line corresponding to that bin. Counts which are high enough probably represent real lines in the image, even if parts of the line are missing. So you just scan through the bins to find bins which exceed the threshold.

OpenCV contains Hough detectors for straight lines and circles, but not for rectangles. You could either use the line detector and check for 4 lines that form the edges of your document; or you could write your own Hough detector for rectangles, perhaps using the paper Jung 2004 for inspiration. Rectangles have at least 5 degrees of freedom (2D position, scale, aspect ratio, and rotation angle), and memory requirement for a 5D array obviously goes up pretty fast. But since the range of each parameter is limited (ie, the document's aspect ratio is known, and you can assume the document will be well centered and not rotated much) it is probably feasible.

Upvotes: 1

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