OpenCV: Using Hough Circle Transformation to detect iris

Question

I am newbie to openCV, but I want to create iris recognition program. Although the system with webcam can detect the eyes, it cannot, however, detect the circular iris. I am using the Hough Circle Transformation. But in case iris in an image is not circular enough, system can't detect it. Any solution for it?

the algorithm used is Hough Circle Transformation.

IplImage *capturedImg = cvLoadImage("circle.jpg",1);
IplImage *grayscaleImg = cvCreateImage(cvGetSize(capturedImg), 8, 1);

cvCvtColor(capturedImg, grayscaleImg, CV_BGR2GRAY);

// Gaussian filter for less noise
cvSmooth(grayscaleImg, grayscaleImg, CV_GAUSSIAN,9, 9 );

//Detect the circles in the image
CvSeq* circles = cvHoughCircles(grayscaleImg,
                         storage,
                         CV_HOUGH_GRADIENT,
                         2,
                         grayscaleImg->height/4,
                         200,
                     100 );

for (i = 0; i < circles->total; i++) 
{
     float* p = (float*)cvGetSeqElem( circles, i );
     cvCircle( capturedImg, cvPoint(cvRound(p[0]),cvRound(p[1])), 
        3, CV_RGB(0,255,0), -1, 8, 0 );
     cvCircle( capturedImg, cvPoint(cvRound(p[0]),cvRound(p[1])), 
         cvRound(p[2]), CV_RGB(0,0,255), 3, 8, 0 );
}
// cvCircle( img,cvPoint( r->x, r->y ),67, CV_RGB(255,0,0), 3, 8, 0 );      
cvNamedWindow( "circles", 1 );
cvShowImage( "circles", capturedImg );

Answer 1

Add a call to cvCanny() between cvSmooth() and cvHoughCircles(). This will execute an edge detection algorithm which is going to provide a better input image for cvHoughCircles() and will probably improve your results.

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