init - 初始化项目

doc/tutorials/imgproc/imgtrans/hough_circle/hough_circle.markdown

@@ -0,0 +1,182 @@
+Hough Circle Transform {#tutorial_hough_circle}
+======================
+
+@tableofcontents
+
+@prev_tutorial{tutorial_hough_lines}
+@next_tutorial{tutorial_remap}
+
+|    |    |
+| -: | :- |
+| Original author | Ana Huamán |
+| Compatibility | OpenCV >= 3.0 |
+
+Goal
+----
+
+In this tutorial you will learn how to:
+
+-   Use the OpenCV function **HoughCircles()** to detect circles in an image.
+
+Theory
+------
+
+### Hough Circle Transform
+
+-   The Hough Circle Transform works in a *roughly* analogous way to the Hough Line Transform
+    explained in the previous tutorial.
+-   In the line detection case, a line was defined by two parameters \f$(r, \theta)\f$. In the circle
+    case, we need three parameters to define a circle:
+
+    \f[C : ( x_{center}, y_{center}, r )\f]
+
+    where \f$(x_{center}, y_{center})\f$ define the center position (green point) and \f$r\f$ is the radius,
+    which allows us to completely define a circle, as it can be seen below:
+
+    ![](images/Hough_Circle_Tutorial_Theory_0.jpg)
+
+-   For sake of efficiency, OpenCV implements a detection method slightly trickier than the standard
+    Hough Transform: *The Hough gradient method*, which is made up of two main stages. The first
+    stage involves edge detection and finding the possible circle centers and the second stage finds
+    the best radius for each candidate center. For more details, please check the book *Learning
+    OpenCV* or your favorite Computer Vision bibliography
+
+####  What does this program do?
+-   Loads an image and blur it to reduce the noise
+-   Applies the *Hough Circle Transform* to the blurred image .
+-   Display the detected circle in a window.
+
+Code
+----
+
+@add_toggle_cpp
+The sample code that we will explain can be downloaded from
+[here](https://raw.githubusercontent.com/opencv/opencv/master/samples/cpp/tutorial_code/ImgTrans/houghcircles.cpp).
+A slightly fancier version (which shows trackbars for changing the threshold values) can be found
+[here](https://raw.githubusercontent.com/opencv/opencv/master/samples/cpp/tutorial_code/ImgTrans/HoughCircle_Demo.cpp).
+@include samples/cpp/tutorial_code/ImgTrans/houghcircles.cpp
+@end_toggle
+
+@add_toggle_java
+The sample code that we will explain can be downloaded from
+[here](https://raw.githubusercontent.com/opencv/opencv/master/samples/java/tutorial_code/ImgTrans/HoughCircle/HoughCircles.java).
+@include samples/java/tutorial_code/ImgTrans/HoughCircle/HoughCircles.java
+@end_toggle
+
+@add_toggle_python
+The sample code that we will explain can be downloaded from
+[here](https://raw.githubusercontent.com/opencv/opencv/master/samples/python/tutorial_code/ImgTrans/HoughCircle/hough_circle.py).
+@include samples/python/tutorial_code/ImgTrans/HoughCircle/hough_circle.py
+@end_toggle
+
+Explanation
+-----------
+
+The image we used can be found [here](https://raw.githubusercontent.com/opencv/opencv/master/samples/data/smarties.png)
+
+####  Load an image:
+
+@add_toggle_cpp
+@snippet samples/cpp/tutorial_code/ImgTrans/houghcircles.cpp load
+@end_toggle
+
+@add_toggle_java
+@snippet samples/python/tutorial_code/ImgTrans/HoughCircle/hough_circle.py load
+@end_toggle
+
+@add_toggle_python
+@snippet samples/java/tutorial_code/ImgTrans/HoughCircle/HoughCircles.java load
+@end_toggle
+
+####  Convert it to grayscale:
+
+@add_toggle_cpp
+@snippet samples/cpp/tutorial_code/ImgTrans/houghcircles.cpp convert_to_gray
+@end_toggle
+
+@add_toggle_java
+@snippet samples/python/tutorial_code/ImgTrans/HoughCircle/hough_circle.py convert_to_gray
+@end_toggle
+
+@add_toggle_python
+@snippet samples/java/tutorial_code/ImgTrans/HoughCircle/HoughCircles.java convert_to_gray
+@end_toggle
+
+#### Apply a Median blur to reduce noise and avoid false circle detection:
+
+@add_toggle_cpp
+@snippet samples/cpp/tutorial_code/ImgTrans/houghcircles.cpp reduce_noise
+@end_toggle
+
+@add_toggle_java
+@snippet samples/python/tutorial_code/ImgTrans/HoughCircle/hough_circle.py reduce_noise
+@end_toggle
+
+@add_toggle_python
+@snippet samples/java/tutorial_code/ImgTrans/HoughCircle/HoughCircles.java reduce_noise
+@end_toggle
+
+#### Proceed to apply Hough Circle Transform:
+
+@add_toggle_cpp
+@snippet samples/cpp/tutorial_code/ImgTrans/houghcircles.cpp houghcircles
+@end_toggle
+
+@add_toggle_java
+@snippet samples/python/tutorial_code/ImgTrans/HoughCircle/hough_circle.py houghcircles
+@end_toggle
+
+@add_toggle_python
+@snippet samples/java/tutorial_code/ImgTrans/HoughCircle/HoughCircles.java houghcircles
+@end_toggle
+
+-   with the arguments:
+
+    -   *gray*: Input image (grayscale).
+    -   *circles*: A vector that stores sets of 3 values: \f$x_{c}, y_{c}, r\f$ for each detected
+        circle.
+    -   *HOUGH_GRADIENT*: Define the detection method. Currently this is the only one available in
+        OpenCV.
+    -   *dp = 1*: The inverse ratio of resolution.
+    -   *min_dist = gray.rows/16*: Minimum distance between detected centers.
+    -   *param_1 = 200*: Upper threshold for the internal Canny edge detector.
+    -   *param_2* = 100\*: Threshold for center detection.
+    -   *min_radius = 0*: Minimum radius to be detected. If unknown, put zero as default.
+    -   *max_radius = 0*: Maximum radius to be detected. If unknown, put zero as default.
+
+####  Draw the detected circles:
+
+@add_toggle_cpp
+@snippet samples/cpp/tutorial_code/ImgTrans/houghcircles.cpp draw
+@end_toggle
+
+@add_toggle_java
+@snippet samples/python/tutorial_code/ImgTrans/HoughCircle/hough_circle.py draw
+@end_toggle
+
+@add_toggle_python
+@snippet samples/java/tutorial_code/ImgTrans/HoughCircle/HoughCircles.java draw
+@end_toggle
+
+You can see that we will draw the circle(s) on red and the center(s) with a small green dot
+
+####  Display the detected circle(s) and wait for the user to exit the program:
+
+@add_toggle_cpp
+@snippet samples/cpp/tutorial_code/ImgTrans/houghcircles.cpp display
+@end_toggle
+
+@add_toggle_java
+@snippet samples/python/tutorial_code/ImgTrans/HoughCircle/hough_circle.py display
+@end_toggle
+
+@add_toggle_python
+@snippet samples/java/tutorial_code/ImgTrans/HoughCircle/HoughCircles.java display
+@end_toggle
+
+Result
+------
+
+The result of running the code above with a test image is shown below:
+
+![](images/Hough_Circle_Tutorial_Result.png)