image processing to improve tesseract OCR accuracy

Question

I\'ve been using tesseract to convert documents into text. The quality of the documents ranges wildly, and I\'m looking for tips on what sort of image processing might impr

Answer 1

As a rule of thumb, I usually apply the following image pre-processing techniques using OpenCV library:

1. Rescaling the image (it's recommended if you’re working with images that have a DPI of less than 300 dpi):

   img = cv2.resize(img, None, fx=1.2, fy=1.2, interpolation=cv2.INTER_CUBIC)
   

2. Converting image to grayscale:

   img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
   

3. Applying dilation and erosion to remove the noise (you may play with the kernel size depending on your data set):

   kernel = np.ones((1, 1), np.uint8)
   img = cv2.dilate(img, kernel, iterations=1)
   img = cv2.erode(img, kernel, iterations=1)
   

4. Applying blur, which can be done by using one of the following lines (each of which has its pros and cons, however, median blur and bilateral filter usually perform better than gaussian blur.):

   cv2.threshold(cv2.GaussianBlur(img, (5, 5), 0), 0, 255, cv2.THRESH_BINARY + cv2.THRESH_OTSU)[1]
   
   cv2.threshold(cv2.bilateralFilter(img, 5, 75, 75), 0, 255, cv2.THRESH_BINARY + cv2.THRESH_OTSU)[1]
   
   cv2.threshold(cv2.medianBlur(img, 3), 0, 255, cv2.THRESH_BINARY + cv2.THRESH_OTSU)[1]
   
   cv2.adaptiveThreshold(cv2.GaussianBlur(img, (5, 5), 0), 255, cv2.ADAPTIVE_THRESH_GAUSSIAN_C, cv2.THRESH_BINARY, 31, 2)
   
   cv2.adaptiveThreshold(cv2.bilateralFilter(img, 9, 75, 75), 255, cv2.ADAPTIVE_THRESH_GAUSSIAN_C, cv2.THRESH_BINARY, 31, 2)
   
   cv2.adaptiveThreshold(cv2.medianBlur(img, 3), 255, cv2.ADAPTIVE_THRESH_GAUSSIAN_C, cv2.THRESH_BINARY, 31, 2)
   

I've recently written a pretty simple guide to Tesseract but it should enable you to write your first OCR script and clear up some hurdles that I experienced when things were less clear than I would have liked in the documentation.

In case you'd like to check them out, here I'm sharing the links with you:

• Getting started with Tesseract - Part I: Introduction

• Getting started with Tesseract - Part II: Image Pre-processing