Improving threshold result for Tesseract

I am kind of stuck with this problem, and I know there are so many questions about it on stack overflow but in my case. Nothing gives the expected result.

The Context:

Am using Android OpenCV along with Tesseract so I can read the MRZ area in the passport. When the camera is started I pass the input frame to an AsyncTask, the frame is processed, the MRZ area is extracted succesfully, I pass the extracted MRZ area to a function prepareForOCR(inputImage) that takes the MRZ area as gray Mat and Will output a bitmap with the thresholded image that I will pass to Tesseract.

The problem:

The problem is while thresholding the Image, I use adaptive thresholding with blockSize = 13 and C = 15, but the result given is not always the same depending on the lighting of the image and the conditions in general from which the frame is taken.

What I have tried:

First I am resizing the image to a specific size (871,108) so the input image is always the same and not dependant on which phone is used. After resizing, I try with different BlockSize and C values

            //toOcr contains the extracted MRZ area
            Bitmap toOCRBitmap = Bitmap.createBitmap(bitmap);
            Mat inputFrame = new Mat();
            Mat toOcr = new Mat();
            Utils.bitmapToMat(toOCRBitmap, inputFrame);
            Imgproc.cvtColor(inputFrame, inputFrame, Imgproc.COLOR_BGR2GRAY);
            TesseractResult lastResult = null;
            for (int B = 11; B < 70; B++) {
                for (int C = 11; C < 70; C++){
                    if (IsPrime(B) && IsPrime(C)){
                        Imgproc.adaptiveThreshold(inputFrame, toOcr, 255, Imgproc.ADAPTIVE_THRESH_GAUSSIAN_C, Imgproc.THRESH_BINARY, B ,C);
                        Bitmap toOcrBitmap = OpenCVHelper.getBitmap(toOcr);
                        TesseractResult result = TesseractInstance.extractFrame(toOcrBitmap, "ocrba");
                        if (result.getMeanConfidence()> 70) {
                            if (MrzParser.tryParse(result.getText())){
                                Log.d("Main2Activity", "Best result with " + B + " : " + C);
                                return result;
                            }
                        }
                    }
                }
            }

Using the code below, the thresholded result image is a black on white image which gives a confidence greater than 70, I can't really post the whole image for privacy reasons, but here's a clipped one and a dummy password one.

Using the MrzParser.tryParse function which adds checks for the character position and its validity within the MRZ, am able to correct some occurences like a name containing a 8 instead of B, and get a good result but it takes so much time, which is normal because am thresholding almost 255 images in the loop, adding to that the Tesseract call.

I already tried getting a list of C and B values which occurs the most but the results are different.

The question:

Is there a way to define a C and blocksize value so that it s always giving the same result, maybe adding more OpenCV calls so The input image like increasing contrast and so on, I searched the web for 2 weeks now I can't find a viable solution, this is the only one that is giving accurate results

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