OpenCV  4.1.0-dev
Open Source Computer Vision
More Morphology Transformations

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Goal

In this tutorial you will learn how to:

Theory

Note
The explanation below belongs to the book Learning OpenCV by Bradski and Kaehler.

In the previous tutorial we covered two basic Morphology operations:

Based on these two we can effectuate more sophisticated transformations to our images. Here we discuss briefly 5 operations offered by OpenCV:

Opening

Closing

Morphological Gradient

Top Hat

Black Hat

Code

Explanation

  1. Let's check the general structure of the C++ program:
    • Load an image
    • Create a window to display results of the Morphological operations
    • Create three Trackbars for the user to enter parameters:
      • The first trackbar Operator returns the kind of morphology operation to use (morph_operator).
        createTrackbar("Operator:\n 0: Opening - 1: Closing \n 2: Gradient - 3: Top Hat \n 4: Black Hat", window_name, &morph_operator, max_operator, Morphology_Operations );
      • The second trackbar Element returns morph_elem, which indicates what kind of structure our kernel is:
        createTrackbar( "Element:\n 0: Rect - 1: Cross - 2: Ellipse", window_name,
        &morph_elem, max_elem,
        Morphology_Operations );
      • The final trackbar Kernel Size returns the size of the kernel to be used (morph_size)
        createTrackbar( "Kernel size:\n 2n +1", window_name,
        &morph_size, max_kernel_size,
        Morphology_Operations );
    • Every time we move any slider, the user's function Morphology_Operations will be called to effectuate a new morphology operation and it will update the output image based on the current trackbar values.
      void Morphology_Operations( int, void* )
      {
      // Since MORPH_X : 2,3,4,5 and 6
      int operation = morph_operator + 2;
      Mat element = getStructuringElement( morph_elem, Size( 2*morph_size + 1, 2*morph_size+1 ), Point( morph_size, morph_size ) );
      morphologyEx( src, dst, operation, element );
      imshow( window_name, dst );
      }
      We can observe that the key function to perform the morphology transformations is cv::morphologyEx . In this example we use four arguments (leaving the rest as defaults):
      • src : Source (input) image
      • dst: Output image
      • operation: The kind of morphology transformation to be performed. Note that we have 5 alternatives:

        • Opening: MORPH_OPEN : 2
        • Closing: MORPH_CLOSE: 3
        • Gradient: MORPH_GRADIENT: 4
        • Top Hat: MORPH_TOPHAT: 5
        • Black Hat: MORPH_BLACKHAT: 6

        As you can see the values range from <2-6>, that is why we add (+2) to the values entered by the Trackbar:

        int operation = morph_operator + 2;
      • element: The kernel to be used. We use the function cv::getStructuringElement to define our own structure.

Results