2019-03-16 19:41:14 -0600 | received badge | ● Popular Question (source) |
2014-05-10 05:37:39 -0600 | commented answer | Finding the center of eye pupil Does not work for me |
2014-05-01 17:19:37 -0600 | asked a question | Finding the center of eye pupil I want to find the center of eye pupil. Here are the steps that I followed: 1- Obtained eye image from the extracted face image: 2- Thresholding the grayscale eye image with the following settings: Max value: 255 Threshold: 60 Threshold Type: CV_THRESH_BINARY 3- I can't find the contour of the eye pupil from the image above. So I applied dilatation first opencv_imgproc.cvDilate(left_eye, left_eye, null, 3); 4- Need to rescale it: opencv_imgproc.cvErode(left_eye, left_eye, null, 6); Now the problem is to find eye center as fast as possible. How can I achieve such a goal? |
2014-04-20 18:25:29 -0600 | asked a question | Equivalent of cv::PCA in JavaCV I am converting codes written in C++ to Java for an Android application. I could not find the equivalent of cv::PCA at line 152. What is the equivalent of PCA class in JavaCV? .cpp source: https://github.com/Itseez/opencv/blob/master/samples/cpp/pca.cpp#L129 |
2013-05-25 06:22:05 -0600 | received badge | ● Editor (source) |
2013-05-23 16:44:48 -0600 | asked a question | Can not distinguish two insects by using SIFT I wan to create a classifier in order to identify an insect by its captured image. At the first time, I used HuMomemnts but images captured in different resolutions gave incorrect results since HuMoments are scale variant. After doing some search on the internet, I found that usage SIFT and SURF can solve my problem and thus, I tried to see what happens when I use SIFT. The first two images below belongs to to different insect kind. The results was bizarre since all features out of 400 were matching (see 3rd image).
} Question 1: Why all of the features are matching in these two images? Question 2: How can I store(i.e. XML file) features of an image in a way that the features can be stored in order to train them in a classification tree (i.e. random tree)? EDIT:
Working on grayscale images does not give different results. Matching 2 same kind of insects and matching 2 different kind of insects produces same number of matches. |