diff --git a/Modules/Applications/AppClassification/app/otbKMeansClassification.cxx b/Modules/Applications/AppClassification/app/otbKMeansClassification.cxx
index ac9d1d7177ecd7035a6b4d13de998c5b93e724fa..58a875b543c33ec3ded4b09d22083d7d226cb48a 100644
--- a/Modules/Applications/AppClassification/app/otbKMeansClassification.cxx
+++ b/Modules/Applications/AppClassification/app/otbKMeansClassification.cxx
@@ -106,7 +106,7 @@ public:
   {
     ShareParameter("ram", "polystats.ram");
     ShareParameter("sampler", "select.sampler");
-    ShareParameter("centroids.out", "training.classifier.sharkkm.centroids.out");
+    ShareParameter("centroids.out", "training.classifier.sharkkm.outcentroids");
     ShareParameter("vm", "polystats.mask", "Validity Mask", "Validity mask, only non-zero pixels will be used to estimate KMeans modes.");
   }
 
@@ -248,10 +248,10 @@ public:
     GetInternalApplication("training")->SetParameterInt("classifier.sharkkm.k", GetParameterInt("nc"));
     if (IsParameterEnabled("centroids.in") && HasValue("centroids.in"))
     {
-      GetInternalApplication("training")->SetParameterString("classifier.sharkkm.centroids.in", GetParameterString("centroids.in"));
+      GetInternalApplication("training")->SetParameterString("classifier.sharkkm.incentroids", GetParameterString("centroids.in"));
 
       GetInternalApplication("training")
-          ->SetParameterString("classifier.sharkkm.centroids.stats", GetInternalApplication("imgstats")->GetParameterString("out"));
+          ->SetParameterString("classifier.sharkkm.cstats", GetInternalApplication("imgstats")->GetParameterString("out"));
     }
 
 
diff --git a/Modules/Applications/AppClassification/include/otbTrainSharkKMeans.hxx b/Modules/Applications/AppClassification/include/otbTrainSharkKMeans.hxx
index 91347c7f7b07f83416de32622418eacbada25544..b517a937cf5c4d04d4152b9e8fc4b5b7c89c9c43 100644
--- a/Modules/Applications/AppClassification/include/otbTrainSharkKMeans.hxx
+++ b/Modules/Applications/AppClassification/include/otbTrainSharkKMeans.hxx
@@ -46,30 +46,26 @@ void LearningApplicationBase<TInputValue, TOutputValue>::InitSharkKMeansParams()
   SetParameterDescription("classifier.sharkkm.k", "The number of classes used for the kmeans algorithm. Default set to 2 class");
   SetMinimumParameterIntValue("classifier.sharkkm.k", 2);
 
-  // Centroid IO
-  AddParameter(ParameterType_Group, "classifier.sharkkm.centroids", "Centroids IO parameters");
-  SetParameterDescription("classifier.sharkkm.centroids", "Group of parameters for centroids IO.");
-
   // Input centroids
-  AddParameter(ParameterType_InputFilename, "classifier.sharkkm.centroids.in", "User definied input centroids");
-  SetParameterDescription("classifier.sharkkm.centroids.in",
+  AddParameter(ParameterType_InputFilename, "classifier.sharkkm.incentroids", "User defined input centroids");
+  SetParameterDescription("classifier.sharkkm.incentroids",
                           "Input text file containing centroid posistions used to initialize the algorithm. "
                           "Each centroid must be described by p parameters, p being the number of features in "
                           "the input vector data, and the number of centroids must be equal to the number of classes "
                           "(one centroid per line with values separated by spaces).");
-  MandatoryOff("classifier.sharkkm.centroids");
+  MandatoryOff("classifier.sharkkm.incentroids");
 
   // Centroid statistics
-  AddParameter(ParameterType_InputFilename, "classifier.sharkkm.centroids.stats", "Statistics file");
-  SetParameterDescription("classifier.sharkkm.centroids.stats",
+  AddParameter(ParameterType_InputFilename, "classifier.sharkkm.cstats", "Statistics file");
+  SetParameterDescription("classifier.sharkkm.cstats",
                           "A XML file containing mean and standard deviation to center"
-                          "and reduce the centroids before the KMeans algorithm, produced by ComputeImagesStatistics application.");
-  MandatoryOff("classifier.sharkkm.centroids.stats");
+                          "and reduce the input centroids before the KMeans algorithm, produced by ComputeImagesStatistics application.");
+  MandatoryOff("classifier.sharkkm.cstats");
 
   // Output centroids
-  AddParameter(ParameterType_OutputFilename, "classifier.sharkkm.centroids.out", "Output centroids text file");
-  SetParameterDescription("classifier.sharkkm.centroids.out", "Output text file containing centroids after the kmean algorithm.");
-  MandatoryOff("classifier.sharkkm.centroids.out");
+  AddParameter(ParameterType_OutputFilename, "classifier.sharkkm.outcentroids", "Output centroids text file");
+  SetParameterDescription("classifier.sharkkm.outcentroids", "Output text file containing centroids after the kmean algorithm.");
+  MandatoryOff("classifier.sharkkm.outcentroids");
 }
 
 template <class TInputValue, class TOutputValue>
@@ -88,14 +84,14 @@ void LearningApplicationBase<TInputValue, TOutputValue>::TrainSharkKMeans(typena
   classifier->SetK(k);
 
   // Initialize centroids from file
-  if (IsParameterEnabled("classifier.sharkkm.centroids.in") && HasValue("classifier.sharkkm.centroids.in"))
+  if (IsParameterEnabled("classifier.sharkkm.incentroids") && HasValue("classifier.sharkkm.incentroids"))
   {
     shark::Data<shark::RealVector> centroidData;
-    shark::importCSV(centroidData, GetParameterString("classifier.sharkkm.centroids.in"), ' ');
-    if (HasValue("classifier.sharkkm.centroids.stats"))
+    shark::importCSV(centroidData, GetParameterString("classifier.sharkkm.incentroids"), ' ');
+    if (HasValue("classifier.sharkkm.cstats"))
     {
       auto statisticsReader = otb::StatisticsXMLFileReader<itk::VariableLengthVector<float>>::New();
-      statisticsReader->SetFileName(GetParameterString("classifier.sharkkm.centroids.stats"));
+      statisticsReader->SetFileName(GetParameterString("classifier.sharkkm.cstats"));
       auto meanMeasurementVector   = statisticsReader->GetStatisticVectorByName("mean");
       auto stddevMeasurementVector = statisticsReader->GetStatisticVectorByName("stddev");
 
@@ -126,8 +122,8 @@ void LearningApplicationBase<TInputValue, TOutputValue>::TrainSharkKMeans(typena
   classifier->Train();
   classifier->Save(modelPath);
 
-  if (HasValue("classifier.sharkkm.centroids.out"))
-    classifier->ExportCentroids(GetParameterString("classifier.sharkkm.centroids.out"));
+  if (HasValue("classifier.sharkkm.outcentroids"))
+    classifier->ExportCentroids(GetParameterString("classifier.sharkkm.outcentroids"));
 }
 
 } // end namespace wrapper