detector/descriptor.

If we have perfect matches (min_dist == 0.0), then strict comparison
fails. Making it non-strict results in treating perfect matches as
good.

sample code : https://github.com/Itseez/opencv/blob/master/samples/cpp/tutorial_code/features2D/SURF_descriptor.cpp

Bug #2888

Tutorial text was not consistent with tutorial source code in samples directory.
Inline source code was replaced on "includeliteral" directive with link to cpp file.

updated links in cheatsheet
renamed directory for Mat tutorial 
changed links from willow docs to opencv.itseez.com, from Trac to current Redmine

Added the "How to write a tutorial for OpenCV?" tutorial. Made some corrections to the feature2D TOC tree. Small visual improvements for the video-write.rst file. Deleted a definition file that served no purpose.

Added the How to create videos with OpenCV Tutorial. Made some corrections to the feature2d, to get rid of some documentation build errors. 

Added tutorial for features2d using homography to find a planar object (Based on the well known find_obj.cpp

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.

Ok, now optimized the tutorial size for real. Made JPG/PNG optimization for all the images. Modified some tutorial files to follow these size optimizations. Now the tutorial PDF generated is 3.95MB, so enjoy!

2) Added a raw Latex page break directive after each TOC tree. (For the PDF tutorial look).
3) Two finished tutorials: 
   a) one describing how the Mat data structure works and its output capabilities (format function) (demonstration YouTube video included).
   b) one describing image scanning operations plus the LUT function (demonstration YouTube video included). 
   c) a basic filtering approach (plus multi row image scanning demonstration) in the work.

Added reST tutorials for Contours (6 in imgproc) and for Corner Detection (4 in features2D) + links in conf.py

New structure (following the documentation) for the tutorials. Normalized image sizes for TOC display.