Add benchmark code for the Chars74k dataset. Using the CNN character classifier reaches 75% and 84% accuracy for case-sensitive and case-insensitive recognition respectively.

Wrap the ROISelector class

Add benchmark for ICDAR2015 dataset using OCRTesseract and ERFilter classes. Gives word spotting f-score 0.642082 with strongly contextualized lexicon (100 words).

Report the total f1 score (0.37) and not the mean-f1. This is in accordance with the standard SVT evaluation protocol and allows for comparison with other published results.

Changes SVT recognition evaluation to be Case Insensitive (according to the standard evaluation protocol). This makes the benchmark obtained mean-f1 score increase from 0.23 to 0.27

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).

Now the filter natively supports StereoBM and StereoSGBM with no
parameter tuning required. Also, now user won't need to set the ROI and
the right matcher parameters manually, it is all done in the respective
convenience factory method based on the left matcher instance. Tutorial
was added to clarify the provided example of use.

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