Using HoughCircles to detect and measure pupil and iris - iphone

Question

I'm trying to use OpenCV, more specifically its HoughCircles to detect and measure the pupil and iris, currently I've been playing with some of the variables in the function, because it either returns 0 circles, or an excessive amount. Below is the code and test image I'm using.
Code for measuring iris:
eye1 = [self increaseIn:eye1 Contrast:2 andBrightness:0];
cv::cvtColor(eye1, eye1, CV_RGBA2RGB);
cv::bilateralFilter(eye1, eye2, 75, 100, 100);
cv::vector<cv::Vec3f> circles;
cv::cvtColor(eye2, eye1, CV_RGBA2GRAY);
cv::morphologyEx(eye1, eye1, 4, cv::getStructuringElement(cv::MORPH_RECT,cv::Size(3, 3)));
cv::threshold(eye1, eye1, 0, 255, cv::THRESH_OTSU);
eye1 = [self circleCutOut:eye1 Size:50];
cv::GaussianBlur(eye1, eye1, cv::Size(7, 7), 0);
cv::HoughCircles(eye1, circles, CV_HOUGH_GRADIENT, 2, eye1.rows/4);
Code for measuring pupil:
eye1 = [self increaseBlackPupil:eye1];
cv::Mat eye2 = cv::Mat::zeros(eye1.rows, eye1.cols, CV_8UC3);
eye1 = [self increaseIn:eye1 Contrast:2 andBrightness:0];
cv::cvtColor(eye1, eye1, CV_RGBA2RGB);
cv::bilateralFilter(eye1, eye2, 75, 100, 100);
cv::threshold(eye2, eye1, 25, 255, CV_THRESH_BINARY);
cv::SimpleBlobDetector::Params params;
params.minDistBetweenBlobs = 75.0f;
params.filterByInertia = false;
params.filterByConvexity = false;
params.filterByCircularity = false;
params.filterByArea = true;
params.minArea = 50;
params.maxArea = 500;
cv::Ptr<cv::FeatureDetector> blob_detector = new cv::SimpleBlobDetector(params);
blob_detector->create("SimpleBlob");
cv::vector<cv::KeyPoint> keypoints;
blob_detector->detect(eye1, keypoints);
I know the image is rough, I've been also trying to find a way to clean it up and make the edges clearer.
So my question to put it plainly: What can I do to adjust the parameters in the function HoughCircles or changes to the images to make the iris and pupil detected?
Thanks

Answer 1

Ok, without experimenting too much, what I understand is that you've only applied a bilateral filter to the image before using the Hough circle detector.
In my opinion, you need to include a thresholding step into the process.
I took your sample image that you provided in the post and made it undergo the following steps:
conversion to greyscale
morphological gradient
thresholding
hough circle detection.
after the thresholding step, I got the following image for the left eye only:
here's the code:
greyscale:
cvCvtColor(im_rgb,im_rgb,CV_RGB2GRAY);
morphology:
cv::morphologyEx(im_rgb,im_rgb,4,cv::getStructuringElement(cv::MORPH_RECT,cv::Size(size,size)));
thresholding:
cv::threshold(im_rgb, im_rgb, low, high, cv::THRESH_OTSU);
hough circle detection:
cv::vector<cv::Vec3f> circles;
cv::HoughCircles(im_rgb, circles, CV_HOUGH_GRADIENT, 2, im_rgb.rows/4);
Now when I print:
NSLog(#"Found %ld cirlces", circles.size());
I get:
"Found 1 cirlces"
Hope this helps.