Merge pull request #11285 from take1014:core_6125

* Resolves 6125

* Fix test code

* Delete unnecessary code

modules/core/src/convert_scale.cpp

@@ -1885,13 +1885,24 @@ void cv::normalize( InputArray _src, InputOutputArray _dst, double a, double b,
     CV_INSTRUMENT_REGION()
 
     double scale = 1, shift = 0;
+    int type = _src.type(), depth = CV_MAT_DEPTH(type);
+
+    if( rtype < 0 )
+        rtype = _dst.fixedType() ? _dst.depth() : depth;
+
     if( norm_type == CV_MINMAX )
     {
         double smin = 0, smax = 0;
         double dmin = MIN( a, b ), dmax = MAX( a, b );
         minMaxIdx( _src, &smin, &smax, 0, 0, _mask );
         scale = (dmax - dmin)*(smax - smin > DBL_EPSILON ? 1./(smax - smin) : 0);
-        shift = dmin - smin*scale;
+        if( rtype == CV_32F )
+        {
+            scale = (float)scale;
+            shift = (float)dmin - (float)(smin*scale);
+        }
+        else
+            shift = dmin - smin*scale;
     }
     else if( norm_type == CV_L2 || norm_type == CV_L1 || norm_type == CV_C )
     {
@@ -1902,10 +1913,6 @@ void cv::normalize( InputArray _src, InputOutputArray _dst, double a, double b,
     else
         CV_Error( CV_StsBadArg, "Unknown/unsupported norm type" );
 
-    int type = _src.type(), depth = CV_MAT_DEPTH(type);
-    if( rtype < 0 )
-        rtype = _dst.fixedType() ? _dst.depth() : depth;
-
     CV_OCL_RUN(_dst.isUMat(),
                ocl_normalize(_src, _dst, _mask, rtype, scale, shift))
 

modules/core/test/test_arithm.cpp

@@ -1918,6 +1918,25 @@ TEST(Normalize, regression_5876_inplace_change_type)
     EXPECT_EQ(0, cvtest::norm(m, result, NORM_INF));
 }
 
+TEST(Normalize, regression_6125)
+{
+    float initial_values[] = {
+        1888, 1692, 369, 263, 199,
+        280, 326, 129, 143, 126,
+        233, 221, 130, 126, 150,
+        249, 575, 574, 63, 12
+    };
+
+    Mat src(Size(20, 1), CV_32F, initial_values);
+    float min = 0., max = 400.;
+    normalize(src, src, 0, 400, NORM_MINMAX, CV_32F);
+    for(int i = 0; i < 20; i++)
+    {
+        EXPECT_GE(src.at<float>(i), min) << "Value should be >= 0";
+        EXPECT_LE(src.at<float>(i), max) << "Value should be <= 400";
+    }
+}
+
 TEST(MinMaxLoc, regression_4955_nans)
 {
     cv::Mat one_mat(2, 2, CV_32F, cv::Scalar(1));