Category: opencv

OpenCV – Distance Transformation The distance transform operator generally takes binary images as inputs. In this operation, the gray level intensities of the points inside the foreground regions are changed to distance their respective distances from the closest 0 value (boundary). You can apply distance transform in OpenCV using the method distanceTransform(). Following is the syntax of this method. distanceTransform(src, dst, distanceType, maskSize) This method accepts the following parameters − src − An object of the class Mat representing the source (input) image. dst − An object of the class Mat representing the destination (output) image. distanceType − A variable of the type integer representing the type of the distance transformation to be applied. maskSize − A variable of integer type representing the mask size to be used. Example The following program demonstrates how to perform distance transformation 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 DistanceTransform { 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/chap19/input.jpg”; Mat src = Imgcodecs.imread(file,0); // Creating an empty matrix to store the results Mat dst = new Mat(); Mat binary = new Mat(); // Converting the grayscale image to binary image Imgproc.threshold(src, binary, 100, 255, Imgproc.THRESH_BINARY); // Applying distance transform Imgproc.distanceTransform(mat, dst, Imgproc.DIST_C, 3); // Writing the image Imgcodecs.imwrite(“E:/OpenCV/chap19/distnceTransform.jpg”, dst); System.out.println(“Image Processed”); } } Assume that following is the input image 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 − Types of Distance Transform Operations In addition to the distance operation type DIST_C demonstrated in the previous example, OpenCV caters various other types of distance transform operations. All these types are represented by predefined static fields (fixed values) of Imgproc class. You can choose the type of the distance transform operation you need, by passing its respective predefined value to the parameter named distanceType of the distanceTransform() method. // Applying distance transform Imgproc.distanceTransform(mat, dst, Imgproc.DIST_C, 3); Following are the values representing various types of distanceTransform operations and their respective outputs. Operation and Description Output DIST_C DIST_L1 DIST_L2 DIST_LABEL_PIXEL DIST_MASK_3 Learning working make money

OpenCV – Morphological Operations In the earlier chapters, we discussed the process of erosion and dilation. In addition to these two, OpenCV has more morphological transformations. The morphologyEx() of the method of the class Imgproc is used to perform these operations on a given image. Following is the syntax of this method − morphologyEx(src, dst, op, kernel) This method accepts the following parameters − src − An object of the class Mat representing the source (input) image. dst − object of the class Mat representing the destination (output) image. op − An integer representing the type of the Morphological operation. kernel − A kernel matrix. Example The following program demonstrates how to apply the morphological operation “top-hat” on an image using OpenCV library. import org.opencv.core.Core; import org.opencv.core.CvType; import org.opencv.core.Mat; import org.opencv.imgcodecs.Imgcodecs; import org.opencv.imgproc.Imgproc; public class MorphologyExTest { 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/chap12/morph_input.jpg”; Mat src = Imgcodecs.imread(file); // Creating an empty matrix to store the result Mat dst = new Mat(); // Creating kernel matrix Mat kernel = Mat.ones(5,5, CvType.CV_32F); // Applying Blur effect on the Image Imgproc.morphologyEx(src, dst, Imgproc.MORPH_TOPHAT, kernel); // Writing the image Imgcodecs.imwrite(“E:/OpenCV/chap12/morph_tophat.jpg”, dst); System.out.println(“Image Processed”); } } Assume that following is the input image morph_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 − More Operations In addition to the morphological operation TOPHAT, demonstrated in the previous example, OpenCV caters various other types of morphologies. All these types are represented by predefined static fields (fixed values) of Imgproc class. You can choose the type of the morphology you need by passing their respective predefined value to the parameter op of the morphologyEx() method. // Applying Blur effect on the Image Imgproc.morphologyEx(src, dst, Imgproc.MORPH_TOPHAT, kernel); Following are the values representing the type of morphological operations and their respective outputs. Operation and Description Output MORPH_BLACKHAT MORPH_CLOSE MORPH_CROSS MORPH_DILATE MORPH_ELLIPSE MORPH_ERODE MORPH_GRADIENT MORPH_OPEN MORPH_RECT MORPH_TOPHAT Learning working make money