Sample files for image scanning, basic Mat, file I/O. Added Victors removed tutorials back in the system. Some typo fixing.Expanded conf.py with new global links.

doc/tutorials/features2d/detection_of_planar_objects/detection_of_planar_objects.rst

@@ -0,0 +1,72 @@
+.. _detectionOfPlanarObjects:
+
+Detection of planar objects
+***************************
+
+.. highlight:: cpp
+
+The goal of this tutorial is to learn how to use *features2d* and *calib3d* modules for detecting known planar objects in scenes. 
+
+*Test data*: use images in your data folder, for instance, ``box.png`` and ``box_in_scene.png``. 
+
+#.
+    Create a new console project. Read two input images. ::
+
+        Mat img1 = imread(argv[1], CV_LOAD_IMAGE_GRAYSCALE);
+        Mat img2 = imread(argv[2], CV_LOAD_IMAGE_GRAYSCALE);
+
+#.
+    Detect keypoints in both images. ::
+
+        // detecting keypoints
+        FastFeatureDetector detector(15);
+        vector<KeyPoint> keypoints1;
+        detector.detect(img1, keypoints1);
+        
+        ... // do the same for the second image
+
+#.
+    Compute descriptors for each of the keypoints. ::
+
+        // computing descriptors
+        SurfDescriptorExtractor extractor;
+        Mat descriptors1;
+        extractor.compute(img1, keypoints1, descriptors1);
+        
+        ... // process keypoints from the second image as well
+
+#.
+    Now, find the closest matches between descriptors from the first image to the second: ::
+
+        // matching descriptors
+        BruteForceMatcher<L2<float> > matcher;
+        vector<DMatch> matches;
+        matcher.match(descriptors1, descriptors2, matches);
+
+#.
+    Visualize the results: ::
+
+        // drawing the results
+        namedWindow("matches", 1);
+        Mat img_matches;
+        drawMatches(img1, keypoints1, img2, keypoints2, matches, img_matches);
+        imshow("matches", img_matches);
+        waitKey(0);
+
+#.
+    Find the homography transformation between two sets of points: ::
+
+        vector<Point2f> points1, points2;
+        // fill the arrays with the points
+        ....
+        Mat H = findHomography(Mat(points1), Mat(points2), CV_RANSAC, ransacReprojThreshold);
+
+
+#.
+    Create a set of inlier matches and draw them. Use perspectiveTransform function to map points with homography:
+
+        Mat points1Projected;
+        perspectiveTransform(Mat(points1), points1Projected, H);
+
+#.
+    Use ``drawMatches`` for drawing inliers. 

doc/tutorials/features2d/table_of_content_features2d/table_of_content_features2d.rst

@@ -86,6 +86,25 @@ Learn about how to use the feature points  detectors, descriptors and matching f
                      :height: 90pt
                      :width:  90pt
 
++ 
+  .. tabularcolumns:: m{100pt} m{300pt}
+  .. cssclass:: toctableopencv
+
+  ===================== ==============================================
+   |DetectPlanar|       **Title:** :ref:`detectionOfPlanarObjects`
+
+                        *Compatibility:* > OpenCV 2.0
+
+                        *Author:* |Author_VictorE|
+
+                        You will use *features2d* and *calib3d* modules for detecting known planar objects in scenes. 
+
+  ===================== ==============================================
+
+  .. |DetectPlanar| image:: images/detection_of_planar_objects.png
+                     :height: 90pt
+                     :width:  90pt
+
 .. raw:: latex
 
    \pagebreak
@@ -97,3 +116,4 @@ Learn about how to use the feature points  detectors, descriptors and matching f
    ../trackingmotion/good_features_to_track/good_features_to_track.rst
    ../trackingmotion/generic_corner_detector/generic_corner_detector
    ../trackingmotion/corner_subpixeles/corner_subpixeles
+   ../detection_of_planar_objects/detection_of_planar_objects