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