Merge pull request #224 from wswld:2.4

doc/tutorials/imgproc/shapedescriptors/bounding_rects_circles/bounding_rects_circles.rst

@@ -85,7 +85,7 @@ This tutorial code's is shown lines below. You can also download it from `here <
      for( int i = 0; i < contours.size(); i++ )
         { approxPolyDP( Mat(contours[i]), contours_poly[i], 3, true );
           boundRect[i] = boundingRect( Mat(contours_poly[i]) );
-          minEnclosingCircle( contours_poly[i], center[i], radius[i] );
+          minEnclosingCircle( (Mat)contours_poly[i], center[i], radius[i] );
         }
 
 

doc/user_guide/ug_mat.rst

@@ -71,7 +71,9 @@ There are functions in OpenCV, especially from calib3d module, such as ``project
     //... fill the array
     Mat pointsMat = Mat(points);
 
-One can access a point in this matrix using the same method \texttt{Mat::at}: ::
+One can access a point in this matrix using the same method ``Mat::at`` : 
+
+::
 
     Point2f point = pointsMat.at<Point2f>(i, 0);
 
@@ -109,7 +111,7 @@ Selecting a region of interest: ::
     Rect r(10, 10, 100, 100);
     Mat smallImg = img(r);
 
-A convertion from \texttt{Mat} to C API data structures: ::
+A convertion from ``Mat`` to C API data structures: ::
 
     Mat img = imread("image.jpg");
     IplImage img1 = img;
@@ -150,7 +152,7 @@ A call to ``waitKey()`` starts a message passing cycle that waits for a key stro
     double minVal, maxVal;
     minMaxLoc(sobelx, &minVal, &maxVal); //find minimum and maximum intensities
     Mat draw;
-    sobelx.convertTo(draw, CV_8U, 255.0/(maxVal - minVal), -minVal);
+    sobelx.convertTo(draw, CV_8U, 255.0/(maxVal - minVal), -minVal * 255.0/(maxVal - minVal));
 
     namedWindow("image", CV_WINDOW_AUTOSIZE);
     imshow("image", draw);

modules/imgproc/doc/miscellaneous_transformations.rst

@@ -661,7 +661,7 @@ Applies a fixed-level threshold to each array element.
 
     :param dst: output array of the same size and type as ``src``.
 
-    :param thresh: treshold value.
+    :param thresh: threshold value.
 
     :param maxval: maximum value to use with the ``THRESH_BINARY`` and ``THRESH_BINARY_INV`` thresholding types.
 

modules/imgproc/doc/structural_analysis_and_shape_descriptors.rst

@@ -137,7 +137,7 @@ Finds contours in a binary image.
 
     :param contours: Detected contours. Each contour is stored as a vector of points.
 
-    :param hierarchy: Optional output vector containing information about the image topology. It has as many elements as the number of contours. For each contour  ``contours[i]`` , the elements  ``hierarchy[i][0]`` ,  ``hiearchy[i][1]`` ,  ``hiearchy[i][2]`` , and  ``hiearchy[i][3]``  are set to 0-based indices in  ``contours``  of the next and previous contours at the same hierarchical level: the first child contour and the parent contour, respectively. If for a contour  ``i``  there are no next, previous, parent, or nested contours, the corresponding elements of  ``hierarchy[i]``  will be negative.
+    :param hierarchy: Optional output vector, containing information about the image topology. It has as many elements as the number of contours. For each i-th contour  ``contours[i]`` , the elements  ``hierarchy[i][0]`` ,  ``hiearchy[i][1]`` ,  ``hiearchy[i][2]`` , and  ``hiearchy[i][3]``  are set to 0-based indices in  ``contours``  of the next and previous contours at the same hierarchical level, the first child contour and the parent contour, respectively. If for the contour  ``i``  there are no next, previous, parent, or nested contours, the corresponding elements of  ``hierarchy[i]``  will be negative.
 
     :param mode: Contour retrieval mode (if you use Python see also a note below).