Tutorial Hit-or-Miss

doc/tutorials/imgproc/hitOrMiss/hitOrMiss.markdown

 Hit-or-Miss {#tutorial_hitOrMiss}
 =================================
 
+@prev_tutorial{tutorial_opening_closing_hats}
+@next_tutorial{tutorial_morph_lines_detection}
+
 Goal
 ----
 
 In this tutorial you will learn how to find a given configuration or pattern in a binary image by using the Hit-or-Miss transform (also known as Hit-and-Miss transform).
 This transform is also the basis of more advanced morphological operations such as thinning or pruning.
 
-We will use the OpenCV function @ref cv::morphologyEx.
-
-
+We will use the OpenCV function **morphologyEx()** .
 
 Hit-or-Miss theory
 -------------------
 
 Morphological operators process images based on their shape. These operators apply one or more *structuring elements* to an input image to obtain the output image.
 The two basic morphological operations are the *erosion* and the *dilation*. The combination of these two operations generate advanced morphological transformations such as *opening*, *closing*, or *top-hat* transform.
-To know more about these and other basic morphological operations refer to previous tutorials @ref tutorial_erosion_dilatation "here" and @ref tutorial_opening_closing_hats "here".
+To know more about these and other basic morphological operations refer to previous tutorials (@ref tutorial_erosion_dilatation "Eroding and Dilating") and (@ref tutorial_opening_closing_hats "More Morphology Transformations").
 
 The Hit-or-Miss transformation is useful to find patterns in binary images. In particular, it finds those pixels whose neighbourhood matches the shape of a first structuring element \f$B_1\f$
 while not matching the shape of a second structuring element \f$B_2\f$ at the same time. Mathematically, the operation applied to an image \f$A\f$ can be expressed as follows:
@@ -43,11 +44,27 @@ You can see that the pattern is found in just one location within the image.
 Code
 ----
 
-The code corresponding to the previous example is shown below. You can also download it from
-[here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/ImgProc/HitMiss.cpp)
-@include samples/cpp/tutorial_code/ImgProc/HitMiss.cpp
+The code corresponding to the previous example is shown below.
+
+@add_toggle_cpp
+You can also download it from
+[here](https://raw.githubusercontent.com/opencv/opencv/master/samples/cpp/tutorial_code/ImgProc/HitMiss/HitMiss.cpp)
+@include samples/cpp/tutorial_code/ImgProc/HitMiss/HitMiss.cpp
+@end_toggle
+
+@add_toggle_java
+You can also download it from
+[here](https://raw.githubusercontent.com/opencv/opencv/master/samples/java/tutorial_code/ImgProc/HitMiss/HitMiss.java)
+@include samples/java/tutorial_code/ImgProc/HitMiss/HitMiss.java
+@end_toggle
+
+@add_toggle_python
+You can also download it from
+[here](https://raw.githubusercontent.com/opencv/opencv/master/samples/python/tutorial_code/imgProc/HitMiss/hit_miss.py)
+@include samples/python/tutorial_code/imgProc/HitMiss/hit_miss.py
+@end_toggle
 
-As you can see, it is as simple as using the function @ref cv::morphologyEx with the operation type @ref cv::MORPH_HITMISS and the chosen kernel.
+As you can see, it is as simple as using the function **morphologyEx()** with the operation type **MORPH_HITMISS** and the chosen kernel.
 
 Other examples
 --------------

doc/tutorials/imgproc/table_of_content_imgproc.markdown

@@ -31,6 +31,8 @@ In this section you will learn about the image processing (manipulation) functio
 
 -   @subpage tutorial_hitOrMiss
 
+    *Languages:* C++, Java, Python
+
     *Compatibility:* \> OpenCV 2.4
 
     *Author:* Lorena García

samples/cpp/tutorial_code/ImgProc/HitMiss.cpp → samples/cpp/tutorial_code/ImgProc/HitMiss/HitMiss.cpp

@@ -23,15 +23,22 @@ int main(){
     Mat output_image;
     morphologyEx(input_image, output_image, MORPH_HITMISS, kernel);
 
-    const int rate = 10;
+    const int rate = 50;
     kernel = (kernel + 1) * 127;
     kernel.convertTo(kernel, CV_8U);
+
     resize(kernel, kernel, Size(), rate, rate, INTER_NEAREST);
     imshow("kernel", kernel);
+    moveWindow("kernel", 0, 0);
+
     resize(input_image, input_image, Size(), rate, rate, INTER_NEAREST);
     imshow("Original", input_image);
+    moveWindow("Original", 0, 200);
+
     resize(output_image, output_image, Size(), rate, rate, INTER_NEAREST);
     imshow("Hit or Miss", output_image);
+    moveWindow("Hit or Miss", 500, 200);
+
     waitKey(0);
     return 0;
 }

samples/java/tutorial_code/ImgProc/HitMiss/HitMiss.java

+import org.opencv.core.*;
+import org.opencv.highgui.HighGui;
+import org.opencv.imgproc.Imgproc;
+
+class HitMissRun{
+
+    public void run() {
+        Mat input_image = new Mat( 8, 8, CvType.CV_8UC1 );
+        int row = 0, col = 0;
+        input_image.put(row ,col,
+                0, 0, 0, 0, 0, 0, 0, 0,
+                0, 255, 255, 255, 0, 0, 0, 255,
+                0, 255, 255, 255, 0, 0, 0, 0,
+                0, 255, 255, 255, 0, 255, 0, 0,
+                0, 0, 255, 0, 0, 0, 0, 0,
+                0, 0, 255, 0, 0, 255, 255, 0,
+                0, 255, 0, 255, 0, 0, 255, 0,
+                0, 255, 255, 255, 0, 0, 0, 0);
+
+        Mat kernel = new Mat( 3, 3, CvType.CV_16S );
+        kernel.put(row ,col,
+                0, 1, 0,
+                1, -1, 1,
+                0, 1, 0 );
+
+        Mat output_image = new Mat();
+        Imgproc.morphologyEx(input_image, output_image, Imgproc.MORPH_HITMISS, kernel);
+
+        int rate = 50;
+        Core.add(kernel, new Scalar(1), kernel);
+        Core.multiply(kernel, new Scalar(127), kernel);
+        kernel.convertTo(kernel, CvType.CV_8U);
+
+        Imgproc.resize(kernel, kernel, new Size(), rate, rate, Imgproc.INTER_NEAREST);
+        HighGui.imshow("kernel", kernel);
+        HighGui.moveWindow("kernel", 0, 0);
+
+        Imgproc.resize(input_image, input_image, new Size(), rate, rate, Imgproc.INTER_NEAREST);
+        HighGui.imshow("Original", input_image);
+        HighGui.moveWindow("Original", 0, 200);
+
+        Imgproc.resize(output_image, output_image, new Size(), rate, rate, Imgproc.INTER_NEAREST);
+        HighGui.imshow("Hit or Miss", output_image);
+        HighGui.moveWindow("Hit or Miss", 500, 200);
+
+        HighGui.waitKey(0);
+        System.exit(0);
+    }
+}
+
+public class HitMiss
+{
+    public static void main(String[] args) {
+        // load the native OpenCV library
+        System.loadLibrary(Core.NATIVE_LIBRARY_NAME);
+        new HitMissRun().run();
+    }
+}

samples/python/tutorial_code/imgProc/HitMiss/hit_miss.py

+import cv2
+import numpy as np
+
+input_image = np.array((
+    [0, 0, 0, 0, 0, 0, 0, 0],
+    [0, 255, 255, 255, 0, 0, 0, 255],
+    [0, 255, 255, 255, 0, 0, 0, 0],
+    [0, 255, 255, 255, 0, 255, 0, 0],
+    [0, 0, 255, 0, 0, 0, 0, 0],
+    [0, 0, 255, 0, 0, 255, 255, 0],
+    [0,255, 0, 255, 0, 0, 255, 0],
+    [0, 255, 255, 255, 0, 0, 0, 0]), dtype="uint8")
+
+kernel = np.array((
+        [0, 1, 0],
+        [1, -1, 1],
+        [0, 1, 0]), dtype="int")
+
+output_image = cv2.morphologyEx(input_image, cv2.MORPH_HITMISS, kernel)
+
+rate = 50
+kernel = (kernel + 1) * 127
+kernel = np.uint8(kernel)
+
+kernel = cv2.resize(kernel, None, fx = rate, fy = rate, interpolation = cv2.INTER_NEAREST)
+cv2.imshow("kernel", kernel)
+cv2.moveWindow("kernel", 0, 0)
+
+input_image = cv2.resize(input_image, None, fx = rate, fy = rate, interpolation = cv2.INTER_NEAREST)
+cv2.imshow("Original", input_image)
+cv2.moveWindow("Original", 0, 200)
+
+output_image = cv2.resize(output_image, None , fx = rate, fy = rate, interpolation = cv2.INTER_NEAREST)
+cv2.imshow("Hit or Miss", output_image)
+cv2.moveWindow("Hit or Miss", 500, 200)
+
+cv2.waitKey(0)
+cv2.destroyAllWindows()