How Can I Fine-Tune Tesseract OCR for Accurate Digit Recognition?

Tesseract Configuration for Fine-tuning OCR Accuracy

Pytesseract, a widely adopted OCR library, offers robust configuration options to optimize character recognition. To address specific challenges like distinguishing digits from letters, this inquiry seeks guidance on configuring Tesseract effectively.

Multi-Config Setup for Digit-Focused Recognition

The original setup employs both -psm 7 for page segmentation and outputbase digits to restrict output to digits. However, for optimal results:

• Character Recognition: Set psm to 10 to enable single character recognition. This ensures that each character is processed independently.
• Digit Restriction: Use tessedit_char_whitelist=0123456789 to restrict recognition to numbers only. As mentioned, the zero ('0') often poses confusion with the letter 'O'.

Sample Configuration Usage

Here's an illustration of how to implement these configurations using image_to_string:

target = pytesseract.image_to_string(image, lang='eng', boxes=False, \
        config='--psm 10 --oem 3 -c tessedit_char_whitelist=0123456789')

This configuration leverages --psm 10 for character recognition, --oem 3 for Tesseract engine selection, and -c tessedit_char_whitelist=0123456789 to enforce digit restriction. By specifying multiple configurations simultaneously, you can fine-tune Tesseract's behavior to meet your specific requirements.

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