c++ - K-means and EM algorithms -

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how can implement k-means & em algorithms without calling opencv functions image segmentation?

i begin code :

#include opencv2/highgui/highgui.hpp #include iostream  using namespace cv; using namespace std;  int main() {     mat img = imread("testimage.png", 0);     mat label_img;     label_img.create(img.cols, img.rows, cv_8uc1); }

how can continue ?

k-means work iterating 2 steps till convergence, e-step , m-step.

initialization:

assign each pixel, @ random, 1 of k clusters. is, each entry in label_img choose number [0..k-1] @ random.

expectation (e-step)

given assignment of pixels clusters (label_img), can compute center of each cluster (simply mean of pixel values assigned cluster).
@ end of stage you'll have k vectors pointing @ centers of k clusters.

maximization (m-step)

once have k clusters, compute distance of each pixel k centers , assign (by changing respective entry in label_img) center closest pixel.
@ end of stage you'll have new assignment of each pixel clusters (new values of label_img)

you need repeat these 2 steps until label_img not change anymore or if exceed pre-defined number of iterations.


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