diff --git a/modules/imgproc/include/opencv2/imgproc.hpp b/modules/imgproc/include/opencv2/imgproc.hpp
index 14f4067a9..a9fa7ae21 100644
--- a/modules/imgproc/include/opencv2/imgproc.hpp
+++ b/modules/imgproc/include/opencv2/imgproc.hpp
@@ -326,9 +326,7 @@ enum AdaptiveThresholdTypes {
     window) of the \f$\texttt{blockSize} \times \texttt{blockSize}\f$ neighborhood of \f$(x, y)\f$
     minus C . The default sigma (standard deviation) is used for the specified blockSize . See
     cv::getGaussianKernel*/
-    ADAPTIVE_THRESH_GAUSSIAN_C = 1,
-     /** Like ADAPTIVE_THRESH_GAUSSIAN_C except that GaussianBlur use CV_32F for blurring to avoid rounding error*/
-   ADAPTIVE_THRESH_GAUSSIAN_C_FLOAT = 2
+    ADAPTIVE_THRESH_GAUSSIAN_C = 1
 };
 
 //! cv::undistort mode
diff --git a/modules/imgproc/src/thresh.cpp b/modules/imgproc/src/thresh.cpp
index 0eae14546..f9c946a17 100644
--- a/modules/imgproc/src/thresh.cpp
+++ b/modules/imgproc/src/thresh.cpp
@@ -1299,8 +1299,6 @@ void cv::adaptiveThreshold( InputArray _src, OutputArray _dst, double maxValue,
         boxFilter( src, mean, src.type(), Size(blockSize, blockSize),
                    Point(-1,-1), true, BORDER_REPLICATE );
     else if (method == ADAPTIVE_THRESH_GAUSSIAN_C)
-        GaussianBlur(src, mean, Size(blockSize, blockSize), 0, 0, BORDER_REPLICATE);
-    else if (method == ADAPTIVE_THRESH_GAUSSIAN_C_FLOAT)
     {
         Mat srcfloat,meanfloat;
         src.convertTo(srcfloat,CV_32F);