Merge pull request #6305 from rishirajsurti:master

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Maksim Shabunin 2016-04-14 08:42:39 +00:00
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@ -51,6 +51,14 @@ In this section you will learn about the image processing (manipulation) functio
After so much processing, it is time to decide which pixels stay!
- @subpage tutorial_threshold_inRange
*Compatibility:* \> OpenCV 2.0
*Author:* Rishiraj Surti
Thresholding operations using inRange function.
- @subpage tutorial_filter_2d
*Compatibility:* \> OpenCV 2.0

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Thresholding Operations using inRange {#tutorial_threshold_inRange}
=============================
Goal
----
In this tutorial you will learn how to:
- Perform basic thresholding operations using OpenCV function @ref cv::inRange
- Detect an object based on the range of pixel values it has
Theory
-----------
- In the previous tutorial, we learnt how perform thresholding using @ref cv::threshold function.
- In this tutorial, we will learn how to do it using @ref cv::inRange function.
- The concept remains same, but now we add a range of pixel values we need.
Code
----
The tutorial code's is shown lines below. You can also download it from
[here](https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/ImgProc/Threshold_inRange.cpp)
@include samples/cpp/tutorial_code/ImgProc/Threshold_inRange.cpp
Explanation
-----------
-# Let's check the general structure of the program:
- Create two Matrix elements to store the frames
@snippet samples/cpp/tutorial_code/ImgProc/Threshold_inRange.cpp mat
- Capture the video stream from default capturing device.
@snippet samples/cpp/tutorial_code/ImgProc/Threshold_inRange.cpp cap
- Create a window to display the default frame and the threshold frame.
@snippet samples/cpp/tutorial_code/ImgProc/Threshold_inRange.cpp window
- Create trackbars to set the range of RGB values
@snippet samples/cpp/tutorial_code/ImgProc/Threshold_inRange.cpp trackbar
- Until the user want the program to exit do the following
@snippet samples/cpp/tutorial_code/ImgProc/Threshold_inRange.cpp while
- Show the images
@snippet samples/cpp/tutorial_code/ImgProc/Threshold_inRange.cpp show
- For a trackbar which controls the lower range, say for example Red value:
@snippet samples/cpp/tutorial_code/ImgProc/Threshold_inRange.cpp low
- For a trackbar which controls the upper range, say for example Red value:
@snippet samples/cpp/tutorial_code/ImgProc/Threshold_inRange.cpp high
- It is necessary to find the maximum and minimum value to avoid discrepancies such as
the high value of threshold becoming less the low value.
Results
-------
-# After compiling this program, run it. The program will open two windows
-# As you set the RGB range values from the trackbar, the resulting frame will be visible in the other window.
![](images/Threshold_inRange_Tutorial_Result_input.jpeg)
![](images/Threshold_inRange_Tutorial_Result_output.jpeg)

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#include "opencv2/imgproc.hpp"
#include "opencv2/highgui.hpp"
#include <iostream>
#include <stdlib.h>
using namespace std;
using namespace cv;
/** Function Headers */
void on_low_r_thresh_trackbar(int, void *);
void on_high_r_thresh_trackbar(int, void *);
void on_low_g_thresh_trackbar(int, void *);
void on_high_g_thresh_trackbar(int, void *);
void on_low_b_thresh_trackbar(int, void *);
void on_high_b_thresh_trackbar(int, void *);
/** Global Variables */
int low_r=30, low_g=30, low_b=30;
int high_r=100, high_g=100, high_b=100;
/** @function main */
int main()
{
//! [mat]
Mat frame, frame_threshold;
//! [mat]
//! [cap]
VideoCapture cap(0);
//! [cap]
//! [window]
namedWindow("Video Capture", WINDOW_NORMAL);
namedWindow("Object Detection", WINDOW_NORMAL);
//! [window]
//! [trackbar]
//-- Trackbars to set thresholds for RGB values
createTrackbar("Low R","Object Detection", &low_r, 255, on_low_r_thresh_trackbar);
createTrackbar("High R","Object Detection", &high_r, 255, on_high_r_thresh_trackbar);
createTrackbar("Low G","Object Detection", &low_g, 255, on_low_g_thresh_trackbar);
createTrackbar("High G","Object Detection", &high_g, 255, on_high_g_thresh_trackbar);
createTrackbar("Low B","Object Detection", &low_b, 255, on_low_b_thresh_trackbar);
createTrackbar("High B","Object Detection", &high_b, 255, on_high_b_thresh_trackbar);
//! [trackbar]
while(char(waitKey(1))!='q'){
//! [while]
cap>>frame;
if(frame.empty())
break;
//-- Detect the object based on RGB Range Values
inRange(frame,Scalar(low_b,low_g,low_r), Scalar(high_b,high_g,high_r),frame_threshold);
//! [while]
//! [show]
//-- Show the frames
imshow("Video Capture",frame);
imshow("Object Detection",frame_threshold);
//! [show]
}
return 0;
}
//! [low]
/** @function on_low_r_thresh_trackbar */
void on_low_r_thresh_trackbar(int, void *)
{
low_r = min(high_r-1, low_r);
setTrackbarPos("Low R","Object Detection", low_r);
}
//! [low]
//! [high]
/** @function on_high_r_thresh_trackbar */
void on_high_r_thresh_trackbar(int, void *)
{
high_r = max(high_r, low_r+1);
setTrackbarPos("High R", "Object Detection", high_r);
}
//![high]
/** @function on_low_g_thresh_trackbar */
void on_low_g_thresh_trackbar(int, void *)
{
low_g = min(high_g-1, low_g);
setTrackbarPos("Low G","Object Detection", low_g);
}
/** @function on_high_g_thresh_trackbar */
void on_high_g_thresh_trackbar(int, void *)
{
high_g = max(high_g, low_g+1);
setTrackbarPos("High G", "Object Detection", high_g);
}
/** @function on_low_b_thresh_trackbar */
void on_low_b_thresh_trackbar(int, void *)
{
low_b= min(high_b-1, low_b);
setTrackbarPos("Low B","Object Detection", low_b);
}
/** @function on_high_b_thresh_trackbar */
void on_high_b_thresh_trackbar(int, void *)
{
high_b = max(high_b, low_b+1);
setTrackbarPos("High B", "Object Detection", high_b);
}