Posts tagged ‘edge’

Detecting the Dominant points on an image using OpenCV

To detect the dominant points within an image first we must find the edges. In this example the edges are found using cvFindContours. The resulting contours are then processed to find the dominant points along the contour. This is done using the cvFindDominantPoints function, this function implements the IPAN99 algorithm to find the points. A small circle is then drawn at each dominant point.

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

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

	// create gray scale image for edge detection
	IplImage* edge = cvCreateImage(cvGetSize(input), 8,1);

	// create output image
	IplImage* output = cvCreateImage(cvGetSize(input), 8,1);

	// threshold the input image
	cvThreshold(input, edge, 230,255, CV_THRESH_BINARY);
	cvNamedWindow("Threshold", CV_WINDOW_AUTOSIZE);
	cvShowImage("Threshold", edge);

	// generate the contours
	CvMemStorage* storage = cvCreateMemStorage();
	CvSeq* contours = NULL;
	int Nc = cvFindContours(edge, storage, &contours, sizeof(CvContour), CV_RETR_LIST);

	// diplay the contours
	printf("Total contours found = %d\n", Nc);
	cvDrawContours(output, contours, cvScalarAll(255),cvScalarAll(255),10); 

	// generate the dominant points
	CvMemStorage* dominantstorage = cvCreateMemStorage();
	CvSeq* dominant = cvFindDominantPoints(contours, dominantstorage, CV_DOMINANT_IPAN,5,15,5,170);

	printf("dominant total=%d\n", dominant->total);

	// display the dominant points
	int i, idx;
    CvPoint p;
	for ( i = 0; i < dominant->total; i++)
    {
        idx = *(int *) cvGetSeqElem(dominant, i);
        p = *(CvPoint *) cvGetSeqElem(contours, idx);
        cvDrawCircle( output, p , 1, CV_RGB(255,0,0) );
        printf("%d %d %d\n", idx, p.x, p.y);
    }
	
	// show output
	cvNamedWindow("Output", CV_WINDOW_AUTOSIZE);
	cvShowImage("Output", output);

	// wait for user
	cvWaitKey(0); 

	// garbage collection	
	cvReleaseImage(&input);
	cvDestroyWindow("Input");
	cvReleaseImage(&edge);
	cvDestroyWindow("Threshold");
	cvReleaseImage(&output);
	cvDestroyWindow("Output");
	return 0;
}

Input Image

threshold

After threshold

Output

Image Contour detection and display using OpenCV

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