Last Updated : 12 Jul, 2025
Optical Character Recognition (OCR) is a technology used to extract text from images which is used in applications like document digitization, license plate recognition and automated data entry. In this article, we explore how to detect and extract text from images using OpenCV for image processing and Tesseract OCR for text recognition.
Before we start we need to install required libraries using following commands:
Step 1: Importing Required Packages
- !pip install opencv-python
- !pip install pytesseract
- !sudo apt-get install tesseract-ocr
Import the required Python libraries like OpenCV, pytesseract and matplotlib.
Python
import cv2
import pytesseract
from matplotlib import pyplot as plt
Step 2: Loading Image
Now we will load the image using cv2.imread() function. OpenCV loads images in BGR format but matplotlib expects RGB format so we convert it using cv2.cvtColor().
Python
image_path = "/mnt/data/08d702e9-fb88-4a5b-98ce-9ad0bc19afd9.png"
image = cv2.imread(image_path)
image_rgb = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
Step 3: Converting Image to Grayscale
Convert the input image to grayscale to simplify the image and remove color information.
Python
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
print("Grayscale Image:")
cv2_imshow(gray)
Step 4: Displaying Original Image
Let's see original image with the help of matplotlib.
Python
plt.figure(figsize=(10, 6))
plt.imshow(image_rgb)
plt.title("Original Image")
plt.axis("off")
plt.show()
Output:
Sample Image Step 5: Extracting Text from ImageIn this step we extract text from the image with the help of pytesseract.image_to_string().
Python
extracted_text = pytesseract.image_to_string(image_rgb)
print(" Extracted Text:\n")
print(extracted_text)
Output:
extracted text Step 6: Drawing Bounding Boxes Around Detected TextNow we loop through each detected word and draw a blue box around it using cv2.reactangle.
Python
data = pytesseract.image_to_data(image_rgb, output_type=pytesseract.Output.DICT)
n_boxes = len(data['level'])
for i in range(n_boxes):
(x, y, w, h) = (data['left'][i], data['top'][i], data['width'][i], data['height'][i])
cv2.rectangle(image_rgb, (x, y), (x + w, y + h), (255, 0, 0), 2)
Finally this shows the processed image with bounding boxes around the detected text.
Python
plt.figure(figsize=(10, 6))
plt.imshow(image_rgb)
plt.title("Image with Text Bounding Boxes")
plt.axis("off")
plt.show()
Output:
Output ImageGet complete notebook link here :
Notebook: click here.
Sample Image: click here.
Text Detection and Extraction using OpenCV and OCR
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