Use pytesseract OCR to recognize text from an image

Question

I need to use Pytesseract to extract text from this picture:

and the code:

from PIL import Image, ImageEnhance, ImageFilter import pytesseract path = 'pic.gif' img = Image.open(path) img = img.convert('RGBA') pix = img.load() for y in range(img.size[1]):     for x in range(img.size[0]):         if pix[x, y][0] < 102 or pix[x, y][1] < 102 or pix[x, y][2] < 102:             pix[x, y] = (0, 0, 0, 255)         else:             pix[x, y] = (255, 255, 255, 255) img.save('temp.jpg') text = pytesseract.image_to_string(Image.open('temp.jpg')) # os.remove('temp.jpg') print(text) 

and the "temp.jpg" is

Not bad, but the result of print is ,2 WW Not the right text2HHH, so how can I remove those black dots?

Answer 1

Here is my solution:

import pytesseract from PIL import Image, ImageEnhance, ImageFilter  im = Image.open("temp.jpg") # the second one  im = im.filter(ImageFilter.MedianFilter()) enhancer = ImageEnhance.Contrast(im) im = enhancer.enhance(2) im = im.convert('1') im.save('temp2.jpg') text = pytesseract.image_to_string(Image.open('temp2.jpg')) print(text) 

Answer 2

Here's a simple approach using OpenCV and Pytesseract OCR. To perform OCR on an image, its important to preprocess the image. The idea is to obtain a processed image where the text to extract is in black with the background in white. To do this, we can convert to grayscale, apply a slight Gaussian blur, then Otsu's threshold to obtain a binary image. From here, we can apply morphological operations to remove noise. Finally we invert the image. We perform text extraction using the --psm 6 configuration option to assume a single uniform block of text. Take a look here for more options.

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Here's a visualization of the image processing pipeline:

Input image

Convert to grayscale -> Gaussian blur -> Otsu's threshold

Notice how there are tiny specs of noise, to remove them we can perform morphological operations

Finally we invert the image

Result from Pytesseract OCR

2HHH 

Code

import cv2 import pytesseract  pytesseract.pytesseract.tesseract_cmd = r"C:\Program Files\Tesseract-OCR\tesseract.exe"  # Grayscale, Gaussian blur, Otsu's threshold image = cv2.imread('1.png') gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY) blur = cv2.GaussianBlur(gray, (3,3), 0) thresh = cv2.threshold(blur, 0, 255, cv2.THRESH_BINARY_INV + cv2.THRESH_OTSU)[1]  # Morph open to remove noise and invert image kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (3,3)) opening = cv2.morphologyEx(thresh, cv2.MORPH_OPEN, kernel, iterations=1) invert = 255 - opening  # Perform text extraction data = pytesseract.image_to_string(invert, lang='eng', config='--psm 6') print(data)  cv2.imshow('thresh', thresh) cv2.imshow('opening', opening) cv2.imshow('invert', invert) cv2.waitKey()