Tutorial Laplace Operator

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tribta 2017-08-22 00:17:09 +01:00
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Laplace Operator {#tutorial_laplace_operator}
================
@prev_tutorial{tutorial_sobel_derivatives}
@next_tutorial{tutorial_canny_detector}
Goal
----
In this tutorial you will learn how to:
- Use the OpenCV function @ref cv::Laplacian to implement a discrete analog of the *Laplacian
- Use the OpenCV function **Laplacian()** to implement a discrete analog of the *Laplacian
operator*.
Theory
@ -37,7 +40,7 @@ Theory
\f[Laplace(f) = \dfrac{\partial^{2} f}{\partial x^{2}} + \dfrac{\partial^{2} f}{\partial y^{2}}\f]
-# The Laplacian operator is implemented in OpenCV by the function @ref cv::Laplacian . In fact,
-# The Laplacian operator is implemented in OpenCV by the function **Laplacian()** . In fact,
since the Laplacian uses the gradient of images, it calls internally the *Sobel* operator to
perform its computation.
@ -50,25 +53,98 @@ Code
- Applies a Laplacian operator to the grayscale image and stores the output image
- Display the result in a window
@add_toggle_cpp
-# The 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/ImgTrans/Laplace_Demo.cpp)
[here](https://raw.githubusercontent.com/opencv/opencv/master/samples/cpp/tutorial_code/ImgTrans/Laplace_Demo.cpp)
@include samples/cpp/tutorial_code/ImgTrans/Laplace_Demo.cpp
@end_toggle
@add_toggle_java
-# The tutorial code's is shown lines below. You can also download it from
[here](https://raw.githubusercontent.com/opencv/opencv/master/samples/java/tutorial_code/ImgTrans/LaPlace/LaplaceDemo.java)
@include samples/java/tutorial_code/ImgTrans/LaPlace/LaplaceDemo.java
@end_toggle
@add_toggle_python
-# The tutorial code's is shown lines below. You can also download it from
[here](https://raw.githubusercontent.com/opencv/opencv/master/samples/python/tutorial_code/ImgTrans/LaPlace/laplace_demo.py)
@include samples/python/tutorial_code/ImgTrans/LaPlace/laplace_demo.py
@end_toggle
Explanation
-----------
-# Create some needed variables:
@snippet cpp/tutorial_code/ImgTrans/Laplace_Demo.cpp variables
-# Loads the source image:
@snippet cpp/tutorial_code/ImgTrans/Laplace_Demo.cpp load
-# Apply a Gaussian blur to reduce noise:
@snippet cpp/tutorial_code/ImgTrans/Laplace_Demo.cpp reduce_noise
-# Convert the image to grayscale using @ref cv::cvtColor
@snippet cpp/tutorial_code/ImgTrans/Laplace_Demo.cpp convert_to_gray
-# Apply the Laplacian operator to the grayscale image:
@snippet cpp/tutorial_code/ImgTrans/Laplace_Demo.cpp laplacian
where the arguments are:
#### Declare variables
@add_toggle_cpp
@snippet cpp/tutorial_code/ImgTrans/Laplace_Demo.cpp variables
@end_toggle
@add_toggle_java
@snippet samples/java/tutorial_code/ImgTrans/LaPlace/LaplaceDemo.java variables
@end_toggle
@add_toggle_python
@snippet samples/python/tutorial_code/ImgTrans/LaPlace/laplace_demo.py variables
@end_toggle
#### Load source image
@add_toggle_cpp
@snippet cpp/tutorial_code/ImgTrans/Laplace_Demo.cpp load
@end_toggle
@add_toggle_java
@snippet samples/java/tutorial_code/ImgTrans/LaPlace/LaplaceDemo.java load
@end_toggle
@add_toggle_python
@snippet samples/python/tutorial_code/ImgTrans/LaPlace/laplace_demo.py load
@end_toggle
#### Reduce noise
@add_toggle_cpp
@snippet cpp/tutorial_code/ImgTrans/Laplace_Demo.cpp reduce_noise
@end_toggle
@add_toggle_java
@snippet samples/java/tutorial_code/ImgTrans/LaPlace/LaplaceDemo.java reduce_noise
@end_toggle
@add_toggle_python
@snippet samples/python/tutorial_code/ImgTrans/LaPlace/laplace_demo.py reduce_noise
@end_toggle
#### Grayscale
@add_toggle_cpp
@snippet cpp/tutorial_code/ImgTrans/Laplace_Demo.cpp convert_to_gray
@end_toggle
@add_toggle_java
@snippet samples/java/tutorial_code/ImgTrans/LaPlace/LaplaceDemo.java convert_to_gray
@end_toggle
@add_toggle_python
@snippet samples/python/tutorial_code/ImgTrans/LaPlace/laplace_demo.py convert_to_gray
@end_toggle
#### Laplacian operator
@add_toggle_cpp
@snippet cpp/tutorial_code/ImgTrans/Laplace_Demo.cpp laplacian
@end_toggle
@add_toggle_java
@snippet samples/java/tutorial_code/ImgTrans/LaPlace/LaplaceDemo.java laplacian
@end_toggle
@add_toggle_python
@snippet samples/python/tutorial_code/ImgTrans/LaPlace/laplace_demo.py laplacian
@end_toggle
- The arguments are:
- *src_gray*: The input image.
- *dst*: Destination (output) image
- *ddepth*: Depth of the destination image. Since our input is *CV_8U* we define *ddepth* =
@ -77,10 +153,33 @@ Explanation
this example.
- *scale*, *delta* and *BORDER_DEFAULT*: We leave them as default values.
-# Convert the output from the Laplacian operator to a *CV_8U* image:
@snippet cpp/tutorial_code/ImgTrans/Laplace_Demo.cpp convert
-# Display the result in a window:
@snippet cpp/tutorial_code/ImgTrans/Laplace_Demo.cpp display
#### Convert output to a *CV_8U* image
@add_toggle_cpp
@snippet cpp/tutorial_code/ImgTrans/Laplace_Demo.cpp convert
@end_toggle
@add_toggle_java
@snippet samples/java/tutorial_code/ImgTrans/LaPlace/LaplaceDemo.java convert
@end_toggle
@add_toggle_python
@snippet samples/python/tutorial_code/ImgTrans/LaPlace/laplace_demo.py convert
@end_toggle
#### Display the result
@add_toggle_cpp
@snippet cpp/tutorial_code/ImgTrans/Laplace_Demo.cpp display
@end_toggle
@add_toggle_java
@snippet samples/java/tutorial_code/ImgTrans/LaPlace/LaplaceDemo.java display
@end_toggle
@add_toggle_python
@snippet samples/python/tutorial_code/ImgTrans/LaPlace/laplace_demo.py display
@end_toggle
Results
-------

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@ -99,6 +99,8 @@ In this section you will learn about the image processing (manipulation) functio
- @subpage tutorial_laplace_operator
*Languages:* C++, Java, Python
*Compatibility:* \> OpenCV 2.0
*Author:* Ana Huamán

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@ -15,50 +15,53 @@ using namespace cv;
*/
int main( int argc, char** argv )
{
//![variables]
Mat src, src_gray, dst;
int kernel_size = 3;
int scale = 1;
int delta = 0;
int ddepth = CV_16S;
const char* window_name = "Laplace Demo";
//![variables]
//![variables]
// Declare the variables we are going to use
Mat src, src_gray, dst;
int kernel_size = 3;
int scale = 1;
int delta = 0;
int ddepth = CV_16S;
const char* window_name = "Laplace Demo";
//![variables]
//![load]
String imageName("../data/lena.jpg"); // by default
if (argc > 1)
{
imageName = argv[1];
}
src = imread( imageName, IMREAD_COLOR ); // Load an image
//![load]
const char* imageName = argc >=2 ? argv[1] : "../data/lena.jpg";
if( src.empty() )
{ return -1; }
//![load]
src = imread( imageName, IMREAD_COLOR ); // Load an image
//![reduce_noise]
/// Reduce noise by blurring with a Gaussian filter
GaussianBlur( src, src, Size(3,3), 0, 0, BORDER_DEFAULT );
//![reduce_noise]
// Check if image is loaded fine
if(src.empty()){
printf(" Error opening image\n");
printf(" Program Arguments: [image_name -- default ../data/lena.jpg] \n");
return -1;
}
//![load]
//![convert_to_gray]
cvtColor( src, src_gray, COLOR_BGR2GRAY ); // Convert the image to grayscale
//![convert_to_gray]
//![reduce_noise]
// Reduce noise by blurring with a Gaussian filter ( kernel size = 3 )
GaussianBlur( src, src, Size(3, 3), 0, 0, BORDER_DEFAULT );
//![reduce_noise]
/// Apply Laplace function
Mat abs_dst;
//![laplacian]
Laplacian( src_gray, dst, ddepth, kernel_size, scale, delta, BORDER_DEFAULT );
//![laplacian]
//![convert_to_gray]
cvtColor( src, src_gray, COLOR_BGR2GRAY ); // Convert the image to grayscale
//![convert_to_gray]
//![convert]
convertScaleAbs( dst, abs_dst );
//![convert]
/// Apply Laplace function
Mat abs_dst;
//![laplacian]
Laplacian( src_gray, dst, ddepth, kernel_size, scale, delta, BORDER_DEFAULT );
//![laplacian]
//![display]
imshow( window_name, abs_dst );
waitKey(0);
//![display]
//![convert]
// converting back to CV_8U
convertScaleAbs( dst, abs_dst );
//![convert]
return 0;
//![display]
imshow( window_name, abs_dst );
waitKey(0);
//![display]
return 0;
}

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@ -0,0 +1,73 @@
/**
* @file LaplaceDemo.java
* @brief Sample code showing how to detect edges using the Laplace operator
*/
import org.opencv.core.*;
import org.opencv.highgui.HighGui;
import org.opencv.imgcodecs.Imgcodecs;
import org.opencv.imgproc.Imgproc;
class LaplaceDemoRun {
public void run(String[] args) {
//! [variables]
// Declare the variables we are going to use
Mat src, src_gray = new Mat(), dst = new Mat();
int kernel_size = 3;
int scale = 1;
int delta = 0;
int ddepth = CvType.CV_16S;
String window_name = "Laplace Demo";
//! [variables]
//! [load]
String imageName = ((args.length > 0) ? args[0] : "../data/lena.jpg");
src = Imgcodecs.imread(imageName, Imgcodecs.IMREAD_COLOR); // Load an image
// Check if image is loaded fine
if( src.empty() ) {
System.out.println("Error opening image");
System.out.println("Program Arguments: [image_name -- default ../data/lena.jpg] \n");
System.exit(-1);
}
//! [load]
//! [reduce_noise]
// Reduce noise by blurring with a Gaussian filter ( kernel size = 3 )
Imgproc.GaussianBlur( src, src, new Size(3, 3), 0, 0, Core.BORDER_DEFAULT );
//! [reduce_noise]
//! [convert_to_gray]
// Convert the image to grayscale
Imgproc.cvtColor( src, src_gray, Imgproc.COLOR_RGB2GRAY );
//! [convert_to_gray]
/// Apply Laplace function
Mat abs_dst = new Mat();
//! [laplacian]
Imgproc.Laplacian( src_gray, dst, ddepth, kernel_size, scale, delta, Core.BORDER_DEFAULT );
//! [laplacian]
//! [convert]
// converting back to CV_8U
Core.convertScaleAbs( dst, abs_dst );
//! [convert]
//! [display]
HighGui.imshow( window_name, abs_dst );
HighGui.waitKey(0);
//! [display]
System.exit(0);
}
}
public class LaplaceDemo {
public static void main(String[] args) {
// Load the native library.
System.loadLibrary(Core.NATIVE_LIBRARY_NAME);
new LaplaceDemoRun().run(args);
}
}

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@ -0,0 +1,59 @@
"""
@file laplace_demo.py
@brief Sample code showing how to detect edges using the Laplace operator
"""
import sys
import cv2
def main(argv):
# [variables]
# Declare the variables we are going to use
ddepth = cv2.CV_16S
kernel_size = 3
window_name = "Laplace Demo"
# [variables]
# [load]
imageName = argv[0] if len(argv) > 0 else "../data/lena.jpg"
src = cv2.imread(imageName, cv2.IMREAD_COLOR) # Load an image
# Check if image is loaded fine
if src is None:
print ('Error opening image')
print ('Program Arguments: [image_name -- default ../data/lena.jpg]')
return -1
# [load]
# [reduce_noise]
# Remove noise by blurring with a Gaussian filter
src = cv2.GaussianBlur(src, (3, 3), 0)
# [reduce_noise]
# [convert_to_gray]
# Convert the image to grayscale
src_gray = cv2.cvtColor(src, cv2.COLOR_BGR2GRAY)
# [convert_to_gray]
# Create Window
cv2.namedWindow(window_name, cv2.WINDOW_AUTOSIZE)
# [laplacian]
# Apply Laplace function
dst = cv2.Laplacian(src_gray, ddepth, kernel_size)
# [laplacian]
# [convert]
# converting back to uint8
abs_dst = cv2.convertScaleAbs(dst)
# [convert]
# [display]
cv2.imshow(window_name, abs_dst)
cv2.waitKey(0)
# [display]
return 0
if __name__ == "__main__":
main(sys.argv[1:])