Extract horizontal and vertical lines by using morphological operations {#tutorial_moprh_lines_detection}
Extract horizontal and vertical lines by using morphological operations {#tutorial_morph_lines_detection}
=============
=============
@prev_tutorial{tutorial_hitOrMiss}
@next_tutorial{tutorial_pyramids}
Goal
Goal
----
----
In this tutorial you will learn how to:
In this tutorial you will learn how to:
- Apply two very common morphology operators (i.e. Dilation and Erosion), with the creation of custom kernels, in order to extract straight lines on the horizontal and vertical axes. For this purpose, you will use the following OpenCV functions:
- Apply two very common morphology operators (i.e. Dilation and Erosion), with the creation of custom kernels, in order to extract straight lines on the horizontal and vertical axes. For this purpose, you will use the following OpenCV functions:
-@ref cv::erode
-**erode()**
-@ref cv::dilate
-**dilate()**
-@ref cv::getStructuringElement
-**getStructuringElement()**
in an example where your goal will be to extract the music notes from a music sheet.
in an example where your goal will be to extract the music notes from a music sheet.
...
@@ -48,39 +51,144 @@ A structuring element can have many common shapes, such as lines, diamonds, disk
...
@@ -48,39 +51,144 @@ A structuring element can have many common shapes, such as lines, diamonds, disk
Code
Code
----
----
This tutorial code's is shown lines below. You can also download it from [here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/ImgProc/Morphology_3.cpp).
You can also download it from [here](https://raw.githubusercontent.com/opencv/opencv/master/samples/cpp/tutorial_code/ImgProc/morph_lines_detection/Morphology_3.cpp).
You can also download it from [here](https://raw.githubusercontent.com/opencv/opencv/master/samples/java/tutorial_code/ImgProc/morph_lines_detection/Morphology_3.java).
You can also download it from [here](https://raw.githubusercontent.com/opencv/opencv/master/samples/python/tutorial_code/imgProc/morph_lines_detection/morph_lines_detection.py).
@snippet samples/cpp/tutorial_code/ImgProc/morph_lines_detection/Morphology_3.cpp bin
@end_toggle
@add_toggle_java
@snippet samples/java/tutorial_code/ImgProc/morph_lines_detection/Morphology_3.java bin
@end_toggle
@add_toggle_python
@snippet samples/python/tutorial_code/imgProc/morph_lines_detection/morph_lines_detection.py bin
@end_toggle
#### Output images
Now we are ready to apply morphological operations in order to extract the horizontal and vertical lines and as a consequence to separate the the music notes from the music sheet, but first let's initialize the output images that we will use for that reason:
As we specified in the theory in order to extract the object that we desire, we need to create the corresponding structure element. Since we want to extract the horizontal lines, a corresponding structure element for that purpose will have the following shape:
and in the source code this is represented by the following code snippet:
-# Afterwards transform grayscale image to binary. Notice the ~ symbol which indicates that we use the inverse (i.e. bitwise_not) version of it:
As you can see we are almost there. However, at that point you will notice that the edges of the notes are a bit rough. For that reason we need to refine the edges in order to obtain a smoother result:
@snippet samples/cpp/tutorial_code/ImgProc/Morphology_3.cpp bin
-# Now we are ready to apply morphological operations in order to extract the horizontal and vertical lines and as a consequence to separate the the music notes from the music sheet, but first let's initialize the output images that we will use for that reason:
-# As we specified in the theory in order to extract the object that we desire, we need to create the corresponding structure element. Since here we want to extract the horizontal lines, a corresponding structure element for that purpose will have the following shape:
@snippet samples/cpp/tutorial_code/ImgProc/Morphology_3.cpp vert
-# As you can see we are almost there. However, at that point you will notice that the edges of the notes are a bit rough. For that reason we need to refine the edges in order to obtain a smoother result:
