Andrew Seaford

In this example we threshold the image based on the position of the track bar. Then find contours on the image an display the contours as white lines.

#include "stdafx.h"
#include "cv.h"
#include "highgui.h"

// global variables
IplImage* input = NULL;
IplImage* gray = NULL;
int threshold = 100;
CvMemStorage* storage = NULL;

/** trackbar event
 * @param trackbar position
 */
void on_trackbar(int)
{
	
	if (storage == NULL)
	{
		// create storage
		gray = cvCreateImage(cvGetSize(input), 8,1);
		storage = cvCreateMemStorage(0);
	}
	else
	{
		// clear storage
		cvClearMemStorage(storage);
	}

	// convert to gray scale and then threshold
	cvCvtColor(input, gray, CV_BGR2GRAY);
	cvThreshold(gray,gray,threshold,255,CV_THRESH_BINARY);

	// find the edges
	CvSeq* edges = 0;
	cvFindContours(gray, storage, &edges);
	cvZero(gray);
	if (edges)
	{
		// display the edges as whiet lines
		cvDrawContours(gray, edges, cvScalarAll(255),cvScalarAll(255),100);
	}
	cvShowImage("Input", gray);
}

/** main function
 * @param argc arguments
 * @param argv argument values
 * @return exit code
 */
int _tmain(int argc, _TCHAR* argv[])
{
	// open and display input image  
    input = cvLoadImage("test.jpg");  
    cvNamedWindow("Input", CV_WINDOW_AUTOSIZE);  
    cvShowImage("Input", input); 

	// create trackbar callback
	cvCreateTrackbar("Threshold", "Input", &threshold, 255, on_trackbar);
	on_trackbar(0);

	// wait for user
	cvWaitKey(0);

	// garbage collection	
	cvReleaseImage(&input);
	cvDestroyWindow("Input");
	return 0;
}

The input image

Threshold value 100

Threshold value 150

Threshold value 200

The cvThreshold function allows us to reject pixels above or below a set value while keeping the others. In this example the input image is separated into the RGB channels. Then we preform a threshold on the red channel, with a maximum value of 100. The result of this is that all the light areas of the image are removed.

#include "stdafx.h"
#include "cv.h"
#include "highgui.h"

int _tmain(int argc, _TCHAR* argv[])
{
	// open and display input image  
    IplImage* input = cvLoadImage("test.jpg");  
    cvNamedWindow("Input", CV_WINDOW_AUTOSIZE);  
    cvShowImage("Input", input); 

	// create the output images
	IplImage* channel_r = cvCreateImage(cvSize(input->width, input->height), input->depth, 1);
	IplImage* channel_g = cvCreateImage(cvSize(input->width, input->height), input->depth, 1);
	IplImage* channel_b = cvCreateImage(cvSize(input->width, input->height), input->depth, 1);

	// split the image
	cvSplit(input, channel_r, channel_g, channel_b, NULL);
	
	// display image
	cvNamedWindow("Channel R", CV_WINDOW_AUTOSIZE);
	cvShowImage("Channel R", channel_r);
	cvSaveImage("channel_r.png", channel_r);

	// threshold red channel
	IplImage* output = cvCreateImage(cvSize(channel_r->width, channel_r->height), channel_r->depth, 1);
	cvThreshold(channel_r, output, 100,100, CV_THRESH_TRUNC);

	// display the output image
	cvNamedWindow("Output", CV_WINDOW_AUTOSIZE);
	cvShowImage("Output", output);
	cvSaveImage("output.png", output);

	// wait for user
	cvWaitKey(0);

	// garbage collection	
	cvReleaseImage(&input);
	cvDestroyWindow("Input");
	cvReleaseImage(&channel_r);
	cvDestroyWindow("Channel R");
	cvReleaseImage(&output);
	cvDestroyWindow("Output");
	return 0;
}

Input Image

The red channel, before threshold

The red channel, after threshold