Obtain only text and numbers

i work on a car plate recognition project i did some preprocessing before passing cropped image to tesseract but there still lot of unwanted noise and lines that affect the plate number recognition for example i have this original image

after aplying this code

#cropping detected objects and passing into tesseract OCR
A = []
for i in indices:
 i = i[0]
 box = boxes[i]
 x = box[0]
 y = box[1]
 w = box[2]
 h = box[3]
 crop_img = image[y:y+h, x:x+w]
 cv2.imwrite("Crop/crop__" + str(i) + ".jpg",crop_img)
 #Resize the image
 img = cv2.resize(crop_img, None, fx=5, fy=5, interpolation=cv2.INTER_CUBIC)
 #Convert image to grayscale
 gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
 #Convert image to black and white
 roi = cv2.adaptiveThreshold(gray, 255, cv2.ADAPTIVE_THRESH_GAUSSIAN_C, cv2.THRESH_BINARY, 69, 1)
 #saving the roi regions
 cv2.imwrite("Crop/roi__" + str(i) + ".jpg",roi)

 roi = cv2.threshold(roi,0,255,cv2.THRESH_BINARY_INV + cv2.THRESH_OTSU)[1]
 roi = cv2.GaussianBlur(roi, (7, 7), 8)
 #passing to tesseract
 c = py.image_to_string(roi, config = '  --psm 13 ')
 #c = py.image_to_string(roi)

 for x in c:
   if x.isdigit():

i get this result which is affecting badly tesseract (output is 13 0 cs3405)} )

Any suggestions to get the cropped image to a perfect state suitable for the plate recognition ?