Adds example on segmented word recognition. Shows the use of the OCRHMMDecoder with the NM and CNN default classifiers.

Overload the run() method in BaseOCR class in order to adapt to different classifier callbacks. The original run() method accepts only one Mat input image, this is expected to be a binarzed image with black and white text and works both with the OCRTesseract class and the OCRHMMDecoder class when the character classifier callback works with binary images (e.g. NM). The new run() method accepts two Mat input parameters. One for the gray scale (or color) source image and the other for a binary mask where each connected component corresponds to a pre-segmented character in the input image. This way the OCRHMMDecoder is able to work with character classifiers that operate in grey scale (or color) images (e.g. a CNN).

Better CNN model for character recognition. Trained with an augmented dataset by adding translation/scale variations. Updated the croped word recognition with new class numbering (compatible with previous NM classifier).

Fix bug #4373: 

Fix memory leak bug #4420

Fix bug #4373: Error (Assertion failed in resize) when passing very elongated contours to the recognition module

Fixed bug in LSDDetector where mask doesn't remove all undesired lines

update to use the new createOCRHMMTransitionsTable() function, and fix program description in header comments

Adds createOCRHMMTransitionsTable() utility function to create a tailored language model transitions table from a given list of words (lexicon)

TLD Open CL Support

wrap DAISY and LATCH to scripting

Conflicts:
	modules/tracking/src/precomp.hpp
	modules/tracking/src/tldDetector.cpp
	modules/tracking/src/tldDetector.hpp
	modules/tracking/src/tldModel.cpp
	modules/tracking/src/tldModel.hpp

1. Added 2-nd level of parallelization of NN on OpenCL
2. Restructured detector - now all filters work independently:
Variance Filter->Ensemble->NN,  through "buffers"