fix java wrappers for ERFilter, OCRHMMDecoder, OCRBeamSearchDecoder (#1210)

* fix java wrappers for ERFilter, OCRHMMDecoder, OCRBeamSearchDecoder

* fix comments

Classifier implemented as an independednt class from the worspotter.
-Works both on CPU and GPU at expected top performance of 26ms per sample on a GTX 980Ti
-Simple demo for wordspoter added for cpp
-Interactiuve demo added for python

erGrouping python bindings and sample script textdetection.py which mimics the same detection pipeline as in textdetection.cpp

OCRBeamSearchDecoder code refactor: fixes most of the TODOs comments, cleans-up code, and fix a bug in score_segmentation(...) member function.

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).

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

Adds a first implementation of the OCRBeamSearchDecoder class using the Single Layer CNN character classifier described in Coates, Adam, et al. paper: Text detection and character recognition in scene images with unsupervised feature learning, ICDAR 2011