I want to detect eyes irises and their centers using Hough Circle
algorithm.
I'm using this code:
private void houghCircle()
{
Bitmap obtainedBitmap = imagesList.getFirst();
/* convert bitmap to mat */
Mat mat = new Mat(obtainedBitmap.getWidth(),obtainedBitmap.getHeight(),
CvType.CV_8UC1);
Mat grayMat = new Mat(obtainedBitmap.getWidth(), obtainedBitmap.getHeight(),
CvType.CV_8UC1);
Utils.bitmapToMat(obtainedBitmap, mat);
/* convert to grayscale */
int colorChannels = (mat.channels() == 3) ? Imgproc.COLOR_BGR2GRAY : ((mat.channels() == 4) ? Imgproc.COLOR_BGRA2GRAY : 1);
Imgproc.cvtColor(mat, grayMat, colorChannels);
/* reduce the noise so we avoid false circle detection */
Imgproc.GaussianBlur(grayMat, grayMat, new Size(9, 9), 2, 2);
// accumulator value
double dp = 1.2d;
// minimum distance between the center coordinates of detected circles in pixels
double minDist = 100;
// min and max radii (set these values as you desire)
int minRadius = 0, maxRadius = 1000;
// param1 = gradient value used to handle edge detection
// param2 = Accumulator threshold value for the
// cv2.CV_HOUGH_GRADIENT method.
// The smaller the threshold is, the more circles will be
// detected (including false circles).
// The larger the threshold is, the more circles will
// potentially be returned.
double param1 = 70, param2 = 72;
/* create a Mat object to store the circles detected */
Mat circles = new Mat(obtainedBitmap.getWidth(), obtainedBitmap.getHeight(), CvType.CV_8UC1);
/* find the circle in the image */
Imgproc.HoughCircles(grayMat, circles, Imgproc.CV_HOUGH_GRADIENT, dp, minDist, param1, param2, minRadius, maxRadius);
/* get the number of circles detected */
int numberOfCircles = (circles.rows() == 0) ? 0 : circles.cols();
/* draw the circles found on the image */
for (int i=0; i<numberOfCircles; i++) {
/* get the circle details, circleCoordinates[0, 1, 2] = (x,y,r)
* (x,y) are the coordinates of the circle's center
*/
double[] circleCoordinates = circles.get(0, i);
int x = (int) circleCoordinates[0], y = (int) circleCoordinates[1];
Point center = new Point(x, y);
int radius = (int) circleCoordinates[2];
/* circle's outline */
Core.circle(mat, center, radius, new Scalar(0,
255, 0), 4);
/* circle's center outline */
Core.rectangle(mat, new Point(x - 5, y - 5),
new Point(x + 5, y + 5),
new Scalar(0, 128, 255), -1);
}
/* convert back to bitmap */
Utils.matToBitmap(mat, obtainedBitmap);
MediaStore.Images.Media.insertImage(getContentResolver(),obtainedBitmap, "testgray", "gray" );
}
But it doesn't detect iris in all images correctly. Specially, if the iris has a dark color like brown. How can I fix this code to detect the irises and their centers correctly?
EDIT: Here are some sample images (which I got from the web) that shows the performance of the algorithm (Please ignore the landmarks which are represented by the red squares):
In these images the algorithm doesn't detect all irises:
This image shows how the algorithm couldn't detect irises at all:
EDIT 2: Here is a code which uses Canny edge detection, but it causes the app to crash:
private void houghCircle()
{
Mat grayMat = new Mat();
Mat cannyEdges = new Mat();
Mat circles = new Mat();
Bitmap obtainedBitmap = imagesList.getFirst();
/* convert bitmap to mat */
Mat originalBitmap = new Mat(obtainedBitmap.getWidth(),obtainedBitmap.getHeight(),
CvType.CV_8UC1);
//Converting the image to grayscale
Imgproc.cvtColor(originalBitmap,grayMat,Imgproc.COLOR_BGR2GRAY);
Imgproc.Canny(grayMat, cannyEdges,10, 100);
Imgproc.HoughCircles(cannyEdges, circles,
Imgproc.CV_HOUGH_GRADIENT,1, cannyEdges.rows() / 15); //now circles is filled with detected circles.
//, grayMat.rows() / 8);
Mat houghCircles = new Mat();
houghCircles.create(cannyEdges.rows(),cannyEdges.cols()
,CvType.CV_8UC1);
//Drawing lines on the image
for(int i = 0 ; i < circles.cols() ; i++)
{
double[] parameters = circles.get(0,i);
double x, y;
int r;
x = parameters[0];
y = parameters[1];
r = (int)parameters[2];
Point center = new Point(x, y);
//Drawing circles on an image
Core.circle(houghCircles,center,r,
new Scalar(255,0,0),1);
}
//Converting Mat back to Bitmap
Utils.matToBitmap(houghCircles, obtainedBitmap);
MediaStore.Images.Media.insertImage(getContentResolver(),obtainedBitmap, "testgray", "gray" );
}
This is the error I get in the log
FATAL EXCEPTION: Thread-28685
CvException [org.opencv.core.CvException: cv::Exception: /hdd2/buildbot/slaves/slave_ardbeg1/50-SDK/opencv/modules/imgproc/src/color.cpp:3739: error: (-215) scn == 3 || scn == 4 in function void cv::cvtColor(cv::InputArray, cv::OutputArray, int, int)
]
at org.opencv.imgproc.Imgproc.cvtColor_1(Native Method)
at org.opencv.imgproc.Imgproc.cvtColor(Imgproc.java:4598)
Which is caused by this line: Imgproc.cvtColor(originalBitmap,grayMat,Imgproc.COLOR_BGR2GRAY);
Can anyone please tell me how this error can solved? Perhaps adding a canny edge detection will improve the results.
In order to detect the circles, or any other geometric shape, we first need to detect the edges of the objects present in the image. The edges in an image are the points for which there is a sharp change of color. For instance, the edge of a red ball on a white background is a circle.
The circle Hough Transform (CHT) is a basic feature extraction technique used in digital image processing for detecting circles in imperfect images. The circle candidates are produced by “voting” in the Hough parameter space and then selecting local maxima in an accumulator matrix.
Hough circles work better on well defined circles. They are not good with things like iris.
After some thresholding, morphological operations or canny edge detection, feature detection methods like MSER work much better for iris detection.
Here is a similar question with a solution if you are looking for some code.
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