tesseract-ocrHow can I improve the accuracy of Tesseract OCR results?

1. Increase the resolution of the input image: Increasing the resolution of the input image can improve the accuracy of Tesseract OCR results. This can be done by using a higher resolution scanner or camera to capture the image.

2. Improve the contrast of the input image: Increasing the contrast of the input image can also improve the accuracy of Tesseract OCR results. This can be done using image editing software such as Photoshop or GIMP.

3. Pre-process the input image: Pre-processing the input image can improve the accuracy of Tesseract OCR results. This can be done by using image processing techniques such as noise removal, image binarization, and image sharpening.

4. Use language-specific training data: Tesseract OCR can be trained to recognize specific languages. Using language-specific training data can improve the accuracy of Tesseract OCR results.

5. Use page segmentation mode: Tesseract OCR can be configured to use a specific page segmentation mode. Using the appropriate page segmentation mode for the input image can improve the accuracy of Tesseract OCR results.

6. Use a custom dictionary: Tesseract OCR can be configured to use a custom dictionary. Using a custom dictionary can improve the accuracy of Tesseract OCR results.

7. Use a different OCR engine: Tesseract OCR is not the only OCR engine available. Using a different OCR engine may improve the accuracy of OCR results.

Example code

# Pre-process the input image
from PIL import Image

# Load the input image
img = Image.open('image.jpg')

# Apply image sharpening
img = img.filter(ImageFilter.SHARPEN)

# Save the pre-processed image
img.save('image_sharpened.jpg')

Output example

No output.

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