OpenCV - Laplacian Transformation

Laplacian Operator is also a derivative operator which is used to find edges in an image. It is a second order derivative mask. In this mask we have two further classifications one is Positive Laplacian Operator and other is Negative Laplacian Operator.

Unlike other operators Laplacian didn’t take out edges in any particular direction but it takes out edges in following classification.

• Inward Edges
• Outward Edges

You can perform Laplacian Transform operation on an image using the Laplacian() method of the imgproc class, following is the syntax of this method.

Laplacian(src, dst, ddepth)

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.

• ddepth − A variable of the type integer representing depth of the destination image.

Example

The following program demonstrates how to perform Laplace transform operation on a given image.

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

public class LaplacianTest {
   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 ="E:/OpenCV/chap18/laplacian_input.jpg";
      Mat src = Imgcodecs.imread(file);

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

      // Applying GaussianBlur on the Image
      Imgproc.Laplacian(src, dst, 10);

      // Writing the image
      Imgcodecs.imwrite("E:/OpenCV/chap18/laplacian.jpg", dst);

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

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

Output

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

Image Processed

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