diff --git a/modules/bgsegm/src/synthetic_seq.cpp b/modules/bgsegm/src/synthetic_seq.cpp
index 2dd103311c8..f5e2a388cea 100644
--- a/modules/bgsegm/src/synthetic_seq.cpp
+++ b/modules/bgsegm/src/synthetic_seq.cpp
@@ -206,7 +206,7 @@ void SyntheticSequenceGenerator::getNextFrame(OutputArray _frame, OutputArray _g
 
     _gtMask.create(sz, CV_8U);
     Mat gtMask = _gtMask.getMat();
-    gtMask = 0;
+    gtMask.setTo(cv::Scalar::all(0));
     gtMask(Rect(Point2i(pos), objSz)) = 255;
 
     pos += dir * objspeed;
diff --git a/modules/img_hash/src/radial_variance_hash.cpp b/modules/img_hash/src/radial_variance_hash.cpp
index d442595cc71..375cb57a1a9 100644
--- a/modules/img_hash/src/radial_variance_hash.cpp
+++ b/modules/img_hash/src/radial_variance_hash.cpp
@@ -276,9 +276,9 @@ class RadialVarianceHashImpl CV_FINAL : public ImgHashBase::ImgHashImpl
         //Different with PHash, this part reverse the row size and col size,
         //because cv::Mat is row major but not column major
         projections_.create(numOfAngelLine_, D, CV_8U);
-        projections_ = 0;
+        projections_.setTo(cv::Scalar::all(0));
         pixPerLine_.create(1, numOfAngelLine_, CV_32S);
-        pixPerLine_ = 0;
+        pixPerLine_.setTo(cv::Scalar::all(0));
         int const xOff = createOffSet(input.cols);
         int const yOff = createOffSet(input.rows);
 
diff --git a/modules/text/src/erfilter.cpp b/modules/text/src/erfilter.cpp
index 8e8afbe5472..8af72b43cf5 100644
--- a/modules/text/src/erfilter.cpp
+++ b/modules/text/src/erfilter.cpp
@@ -4030,8 +4030,8 @@ void MSERsToERStats(InputArray image, vector<vector<Point> > &contours, vector<v
       mser_regions[1].push_back(cser);
     }
 
-    mask(cser.rect) = 0;
-    mtmp(cser.rect) = 0;
+    mask(cser.rect).setTo(cv::Scalar::all(0));
+    mtmp(cser.rect).setTo(cv::Scalar::all(0));
   }
 }
 
diff --git a/modules/xfeatures2d/src/pct_signatures/pct_clusterizer.cpp b/modules/xfeatures2d/src/pct_signatures/pct_clusterizer.cpp
index 0e2ee36f7ed..58d5d2792f3 100644
--- a/modules/xfeatures2d/src/pct_signatures/pct_clusterizer.cpp
+++ b/modules/xfeatures2d/src/pct_signatures/pct_clusterizer.cpp
@@ -146,10 +146,10 @@ namespace cv
                     {
                         // Prepare space for new centroid values.
                         Mat tmpCentroids(clusters.size(), clusters.type());
-                        tmpCentroids = 0;
+                        tmpCentroids.setTo(cv::Scalar::all(0));
 
                         // Clear weights for new iteration.
-                        clusters(Rect(WEIGHT_IDX, 0, 1, clusters.rows)) = 0;
+                        clusters(Rect(WEIGHT_IDX, 0, 1, clusters.rows)).setTo(cv::Scalar::all(0));
 
                         // Compute affiliation of points and sum new coordinates for centroids.
                         for (int iSample = 0; iSample < samples.rows; iSample++)
diff --git a/modules/ximgproc/src/fast_line_detector.cpp b/modules/ximgproc/src/fast_line_detector.cpp
index 4e345b56ee6..95a46a8429b 100644
--- a/modules/ximgproc/src/fast_line_detector.cpp
+++ b/modules/ximgproc/src/fast_line_detector.cpp
@@ -513,8 +513,8 @@ void FastLineDetectorImpl::lineDetection(const Mat& src, std::vector<SEGMENT>& s
     {
         Canny(src, canny, canny_th1, canny_th2, canny_aperture_size);
     }
-    canny.colRange(0,6).rowRange(0,6) = 0;
-    canny.colRange(src.cols-5,src.cols).rowRange(src.rows-5,src.rows) = 0;
+    canny.colRange(0,6).rowRange(0,6).setTo(cv::Scalar::all(0));
+    canny.colRange(src.cols-5,src.cols).rowRange(src.rows-5,src.rows).setTo(cv::Scalar::all(0));
 
     SEGMENT seg, seg1, seg2;
 
diff --git a/modules/ximgproc/src/seeds.cpp b/modules/ximgproc/src/seeds.cpp
index 268564b3f97..54fac992d25 100644
--- a/modules/ximgproc/src/seeds.cpp
+++ b/modules/ximgproc/src/seeds.cpp
@@ -136,8 +136,8 @@ class SuperpixelSEEDSImpl : public SuperpixelSEEDS
     //compute initial label for sublevels: level <= seeds_top_level
     //this is an equally sized grid with size nr_h[level]*nr_w[level]
     int computeLabel(int level, int x, int y) {
-        return std::min(y / (height / nr_wh[2 * level + 1]), nr_wh[2 * level + 1] - 1) * nr_wh[2 * level]
-                + std::min((x / (width / nr_wh[2 * level])), nr_wh[2 * level] - 1);
+        return std::min(y * nr_wh[2 * level + 1] / height, nr_wh[2 * level + 1] - 1) * nr_wh[2 * level]
+            + std::min(x * nr_wh[2 * level] / width, nr_wh[2 * level] - 1);
     }
     inline int nrLabels(int level) const {
         return nr_wh[2 * level + 1] * nr_wh[2 * level];