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Colour Quantization

asked 2012-12-18 09:36:11 -0500

imran gravatar image

updated 2016-04-13 10:20:39 -0500

LBerger gravatar image

Does anyone know if there are any Colour Quantization (Colour Reduction) methods in OpenCV?

If so, could you please guide me to where it is? Or anyone else that has implemented it using OpenCV?

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answered 2012-12-19 00:17:44 -0500

updated 2012-12-19 02:14:06 -0500

for color quantization without number of color you can use cvPyrMeanShift else quantization with number of color you can use cvKmean.In the KMean method the number of clusters is equal to number of the output colors and convert the input image rows/columns as a set of 1D vectors with 3 component(RGB).You have to use KMean in 3D instead of 2D. For quantization by KMean use the below code.

void bhQuantizeImage(IplImage* srcImage,IplImage* dstImage,int colorCount)
{
     int i, size;

  CvMat *clusters;
  CvMat *points;
  CvMat *color = cvCreateMat (colorCount, 1, CV_32FC3);
  CvMat *count = cvCreateMat (colorCount, 1, CV_32SC1);


  size = srcImage->width * srcImage->height;
  dstImage = cvCloneImage (srcImage);
  clusters = cvCreateMat (size, 1, CV_32SC1);
  points = cvCreateMat (size, 1, CV_32FC3);

  for (i = 0; i < size; i++) {
    points->data.fl[i * 3 + 0] = (uchar) srcImage->imageData[i * 3 + 0];
    points->data.fl[i * 3 + 1] = (uchar) srcImage->imageData[i * 3 + 1];
    points->data.fl[i * 3 + 2] = (uchar) srcImage->imageData[i * 3 + 2];
  }

  cvKMeans2 (points, colorCount, clusters, cvTermCriteria (CV_TERMCRIT_EPS + CV_TERMCRIT_ITER, 10, 1.0));

  cvSetZero (color);
  cvSetZero (count);
  for (i = 0; i < size; i++) {
    int idx = clusters->data.i[i];
    int j = ++count->data.i[idx];;
    color->data.fl[idx * 3 + 0] = color->data.fl[idx * 3 + 0] * (j - 1) / j + points->data.fl[i * 3 + 0] / j;
    color->data.fl[idx * 3 + 1] = color->data.fl[idx * 3 + 1] * (j - 1) / j + points->data.fl[i * 3 + 1] / j;
    color->data.fl[idx * 3 + 2] = color->data.fl[idx * 3 + 2] * (j - 1) / j + points->data.fl[i * 3 + 2] / j;
  }

  for (i = 0; i < size; i++) {
    int idx = clusters->data.i[i];
    dstImage->imageData[i * 3 + 0] = (char) color->data.fl[idx * 3 + 0];
    dstImage->imageData[i * 3 + 1] = (char) color->data.fl[idx * 3 + 1];
    dstImage->imageData[i * 3 + 2] = (char) color->data.fl[idx * 3 + 2];
  }


  cvReleaseMat (&clusters);
  cvReleaseMat (&points);
  cvReleaseMat (&color);
  cvReleaseMat (&count);
}
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Thanks for the guidance.

imran gravatar imageimran ( 2012-12-20 10:02:06 -0500 )edit

Thanks for the detailed answer. If possible though; can some documentation be added to the code to highlight the key tasks for further elaboration?

user1446598 gravatar imageuser1446598 ( 2013-03-31 10:46:45 -0500 )edit
1

answered 2012-12-18 10:28:38 -0500

SR gravatar image

Choose k-colors by using k-means clustering

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Thanks for the guidance

imran gravatar imageimran ( 2012-12-20 10:01:23 -0500 )edit
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Asked: 2012-12-18 09:36:11 -0500

Seen: 5,347 times

Last updated: Dec 19 '12