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Imgproc.HoughCircles(mGray, circles, Imgproc.CV_HOUGH_GRADIENT, 1, 20);

i am using this method, the Java wrapper for the C++ function cvHoughCircles, using this with Android.

what are some ways i can make this method more sensitive for positive detection. i am using it to detect circular objects on a plain wooden desk background, so there is not much in that background to cause a false positive, but i have the opposite problem

i have some circular objects that it will not pick up and wanted to increase the accuracy. so more positive results would bet better.

in addition i found that Imgproc.GaussianBlur(mGray, mGray, new Size(5, 5), 2, 2); was decreasing the sensitivity even more than it was before using it so i removed this method. i did see many examples on the internet that used it.

a little confused about the 4th parameter in the HoughCircle method shown above, in this case the 1, would that have any effect on how sensitive the method is?

Imgproc.HoughCircles(mGray, circles, Imgproc.CV_HOUGH_GRADIENT, 1, 20);

i am using this method, the Java wrapper for the C++ function cvHoughCircles, using this with Android.

what are some ways i can make this method more sensitive for positive detection. i am using it to detect circular objects on a plain wooden desk background, so there is not much in that background to cause a false positive, but i have the opposite problem

i have some circular objects that it will not pick up and wanted to increase the accuracy. so more positive results would bet be better.

in addition i found that Imgproc.GaussianBlur(mGray, mGray, new Size(5, 5), 2, 2); was decreasing the sensitivity even more than it was before using it so i removed this method. i did see many examples on the internet that used it.

a little confused about the 4th parameter in the HoughCircle method shown above, in this case the 1, would that have any effect on how sensitive the method is?

 dp - Inverse ratio of the accumulator resolution to the image resolution.
 For example, if dp=1, the accumulator has the same resolution as the input image. 
 If dp=2, the accumulator has half as big width and height.

Imgproc.HoughCircles(mGray, circles, Imgproc.CV_HOUGH_GRADIENT, 1, 20);

i am using this method, the Java wrapper for the C++ function cvHoughCircles, using this with Android.

what are some ways i can make this method more sensitive for positive detection. i am using it to detect circular objects on a plain wooden desk background, so there is not much in that background to cause a false positive, but i have the opposite problem

i have some circular objects that it will not pick up and wanted to increase the accuracy. so more positive results would be better.

in addition i found that Imgproc.GaussianBlur(mGray, mGray, new Size(5, 5), 2, 2); was decreasing the sensitivity even more than it was before using it so i removed this method. i did see many examples on the internet that used it.

a little confused about the 4th parameter in the HoughCircle method shown above, in this case the 1, would that have any effect on how sensitive the method is?

from the documentation for the 4th parameter,

 dp - Inverse ratio of the accumulator resolution to the image resolution.
 For example, if dp=1, the accumulator has the same resolution as the input image. 
 If dp=2, the accumulator has half as big width and height.