tesseract-ocrHow can I fine tune Tesseract OCR for improved accuracy?

In order to fine tune Tesseract OCR for improved accuracy, the following steps can be taken:

1. Adjust the Page Segmentation Mode (PSM): The PSM determines how Tesseract should interpret the image. The default is PSM 3, which is suitable for most images. However, by changing the PSM to a more specific mode, such as PSM 7, which is suitable for images with a single line of text, Tesseract can be tuned to better recognize the text in the image.

2. Adjust the Tesseract Configuration File: The Tesseract configuration file can be adjusted to fine-tune the OCR engine. For example, the tessedit_char_whitelist parameter can be used to restrict Tesseract to only recognize certain characters.

tessedit_char_whitelist abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ

3. Use Pre-Processing: Pre-processing the image before feeding it to Tesseract can greatly improve the accuracy of the OCR. This can include techniques such as deskewing, binarization, and noise removal.

4. Train Tesseract: Tesseract can be trained to recognize specific fonts or languages. This requires creating a box file with the coordinates of each character in the image, and then feeding it to the Tesseract training tools.

5. Use a Different OCR Engine: If Tesseract does not produce the desired results, another OCR engine, such as Google's Vision API, can be used instead.

Helpful links

• Tesseract OCR Documentation
• Tesseract Training Documentation
• Google Cloud Vision API Documentation

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