Index: modules/core/src/matrix.cpp
===================================================================
--- modules/core/src/matrix.cpp	(revision 6258)
+++ modules/core/src/matrix.cpp	(working copy)
@@ -2259,6 +2259,66 @@
     }
 }
 
+#ifdef HAVE_TBB 
+
+class KMeansDistanceComputer
+{
+  float *distances;
+  int *labels;
+  const cv::Mat& data;
+  const cv::Mat& centers;
+  
+public:
+
+  KMeansDistanceComputer(float *_distances,
+			 int *_labels,
+			 const cv::Mat& _data,
+			 const cv::Mat& _centers)
+    : distances(_distances),
+      labels(_labels),
+      data(_data),
+      centers(_centers)
+  {
+    CV_DbgAssert(centers.cols == data.cols);
+  }
+
+  void operator()(const cv::BlockedRange& range) const
+  {
+    const int begin = range.begin();
+    const int end = range.end();
+    const int K = centers.rows;
+    const int dims = centers.cols;
+
+    const float *sample;
+    for( int i=begin; i<end; ++i) 
+    {
+
+      sample = data.ptr<float>(i);
+      int k_best = 0;
+      double min_dist = DBL_MAX;
+      
+      for( int k = 0; k < K; k++ )
+      {
+	  const float* center = centers.ptr<float>(k);
+	  const double dist = distance(sample, center, dims);
+	  
+	  if( min_dist > dist )
+	  {
+	      min_dist = dist;
+	      k_best = k;
+	  }
+      }
+      
+      distances[i] = min_dist;
+      labels[i] = k_best;
+    }
+    
+  }
+  
+};
+
+#endif //HAVE_TBB
+
 }
     
 double cv::kmeans( InputArray _data, int K,
@@ -2338,6 +2398,10 @@
         }
     }
 
+#ifdef HAVE_TBB 
+    cv::Mat dists(N, 1, CV_32F);
+#endif //HAVE_TBB
+    
     for( a = 0; a < attempts; a++ )
     {
         double max_center_shift = DBL_MAX;
@@ -2422,6 +2486,7 @@
             }
 
             // assign labels
+#ifndef HAVE_TBB 
             compactness = 0;
             for( i = 0; i < N; i++ )
             {
@@ -2444,6 +2509,17 @@
                 compactness += min_dist;
                 labels[i] = k_best;
             }
+#else
+	    float* dist = dists.ptr<float>(0);
+	    cv::parallel_for(cv::BlockedRange(0, N),
+			     KMeansDistanceComputer(dist, labels, data, centers));
+	    compactness = 0;
+	    for( i = 0; i < N; i++ )
+	    {
+	      compactness += dist[i];
+	    }
+
+#endif //HAVE_TBB
         }
 
         if( compactness < best_compactness )