extract text from Driving Licence

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Hi team, I could not able to remove image background(watermark) from Driving Licence.For this reason unable to extract text from image.Could anyone please help me on this.

Below is the sample image and code:

from imutils.object_detection import non_max_suppression
import numpy as np
import pytesseract
pytesseract.pytesseract.tesseract_cmd = r'\Tesseract-OCR\tesseract.exe'
import argparse
import cv2


def decode_predictions(scores, geometry):

    (numRows, numCols) = scores.shape[2:4]
    rects = []
    confidences = []

    for y in range(0, numRows):

        scoresData = scores[0, 0, y]
        xData0 = geometry[0, 0, y]
        xData1 = geometry[0, 1, y]
        xData2 = geometry[0, 2, y]
        xData3 = geometry[0, 3, y]
        anglesData = geometry[0, 4, y]

        for x in range(0, numCols):

            if scoresData[x] < args['min_confidence']:
                continue

            (offsetX, offsetY) = (x * 4.0, y * 4.0)

            angle = anglesData[x]
            cos = np.cos(angle)
            sin = np.sin(angle)

            h = xData0[x] + xData2[x]
            w = xData1[x] + xData3[x]

            endX = int(offsetX + cos * xData1[x] + sin * xData2[x])
            endY = int(offsetY - sin * xData1[x] + cos * xData2[x])
            startX = int(endX - w)
            startY = int(endY - h)

            rects.append((startX, startY, endX, endY))
            confidences.append(scoresData[x])

    return (rects, confidences)


ap = argparse.ArgumentParser()
ap.add_argument('-i', '--image', type=str, help='path to input image')
ap.add_argument('-east', '--east', type=str,
                help='path to input EAST text detector')
ap.add_argument('-c', '--min-confidence', type=float, default=0.5,
                help='minimum probability required to inspect a region')
ap.add_argument('-w', '--width', type=int, default=320,
                help='nearest multiple of 32 for resized width')
ap.add_argument('-e', '--height', type=int, default=320,
                help='nearest multiple of 32 for resized height')
ap.add_argument('-p', '--padding', type=float, default=0.0,
                help='amount of padding to add to each border of ROI')
args = vars(ap.parse_args())

image = cv2.imread(args['image'])
orig = image.copy()
(origH, origW) = image.shape[:2]

(newW, newH) = (args['width'], args['height'])
rW = origW / float(newW)
rH = origH / float(newH)

image = cv2.resize(image, (newW, newH))
(H, W) = image.shape[:2]

layerNames = ['feature_fusion/Conv_7/Sigmoid', 'feature_fusion/concat_3'
              ]

print '[INFO] loading EAST text detector...'
net = cv2.dnn.readNet(args['east'])

blob = cv2.dnn.blobFromImage(
    image,
    1.0,
    (W, H),
    (400, 180, 20),
    swapRB=True,
    crop=False,
    )
net.setInput(blob)
(scores, geometry) = net.forward(layerNames)

(rects, confidences) = decode_predictions(scores, geometry)
boxes = non_max_suppression(np.array(rects), probs=confidences)

results = []

for (startX, startY, endX, endY) in boxes:

    startX = int(startX * rW)
    startY = int(startY * rH)
    endX = int(endX * rW)
    endY = int(endY * rH)

    dX = int((endX - startX) * args['padding'])
    dY = int((endY - startY) * args['padding'])

    startX = max(0, startX - dX)
    startY = max(0, startY - dY)
    endX = min(origW, endX + dX * 2)
    endY = min(origH, endY + dY * 2)

    roi = orig[startY:endY, startX:endX]
    crop_image = orig[startY:endY, startX:endX]

    config = '-l eng --oem 1 --psm 7'
    text = pytesseract.image_to_string(roi, config=config)

    results.append(((startX, startY, endX, endY), text))

results = sorted(results, key=lambda r: r[0][1])

for ((startX, startY, endX, endY), text) in results:

    print 'OCR TEXT'
    print '========'
    print '{}\n'.format(text)

    text = ''.join([(c if ord ...