OpenCV - Erosion

Erosion is quite a similar process as dilation. But the pixel value computed here is minimum rather than maximum in dilation. The image is replaced under the anchor point with that minimum pixel value.

With this procedure, the areas of dark regions grow in size and bright regions reduce. For example, the size of an object in dark shade or black shade increases, while it decreases in white shade or bright shade.

Example

You can perform this operation on an image using the erode() method of the imgproc class. Following is the syntax of this method −

erode(src, dst, kernel)

This method accepts the following parameters −

  • src − A Mat object representing the source (input image) for this operation.

  • dst − A Mat object representing the destination (output image) for this operation.

  • kernel − A Mat object representing the kernel.

You can prepare the kernel matrix using the getStructuringElement() method. This method accepts an integer representing the morph_rect type and an object of the type Size.

Imgproc.getStructuringElement(int shape, Size ksize);

The following program demonstrates how to perform the erosion operation on a given image.

import org.opencv.core.Core;
import org.opencv.core.Mat;
import org.opencv.core.Size;
import org.opencv.imgcodecs.Imgcodecs;
import org.opencv.imgproc.Imgproc;

public class ErodeTest {
   public static void main( String[] args ) {
      // Loading the OpenCV core library
      System.loadLibrary( Core.NATIVE_LIBRARY_NAME );

      // Reading the Image from the file and storing it in to a Matrix object
      String file ="C:/EXAMPLES/OpenCV/sample.jpg";
      Mat src = Imgcodecs.imread(file);

      // Creating an empty matrix to store the result
      Mat dst = new Mat();

      // Preparing the kernel matrix object
      Mat kernel = Imgproc.getStructuringElement(Imgproc.MORPH_RECT, 
         new  Size((2*2) + 1, (2*2)+1));

      // Applying erode on the Image
      Imgproc.erode(src, dst, kernel);

      // Writing the image
      Imgcodecs.imwrite("E:/OpenCV/chap10/Erosion.jpg", dst);

      System.out.println("Image processed");
   }
}

Assume that following is the input image sample.jpg specified in the above program.

Sample Image

Output

On executing the program, you will get the following output −

Image Loaded

If you open the specified path, you can observe the output image as follows −

Erosion
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