Best Practices for Optimizing OCR Accuracy in Document Scanning

by Andrew Henderson
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In today’s digital age, Optical Character Recognition (OCR) technology plays a pivotal role in transforming paper documents into searchable and editable digital formats. Whether you’re a business looking to streamline document management or an individual digitizing your personal files, ensuring high OCR accuracy is crucial. In this article, we will explore the best practices to optimize OCR accuracy in document scanning.

Choose High-Quality Scanners

The first step in achieving accurate OCR results is to invest in high-quality document scanners. Low-quality scanners may introduce artifacts, smudges, or distortion into the scanned image, making it challenging for OCR software to recognize characters accurately. Opt for scanners with features like optical resolution, duplex scanning, and automatic document feeders (ADF) to ensure the best image quality.

Use Proper Scanning Settings

Setting up your scanner correctly is equally important. Always scan documents in grayscale or black and white mode, as color images can lead to larger file sizes and may confuse OCR algorithms. Adjust the scanning resolution to a minimum of 300 DPI (dots per inch) for text documents to capture fine details. Additionally, ensure that the documents are scanned in a straight orientation to avoid skewing, which can affect OCR accuracy.

Clean and Prepare Documents

Before scanning, make sure the documents are clean and free from dust, stains, or creases. Any imperfections on the paper can hinder OCR recognition. Straighten out folded pages, remove staples or paperclips, and ensure the pages are well-aligned in the feeder. Cleaning the scanner’s glass and rollers regularly will also help maintain image clarity.

Choose the Right OCR Software

Selecting the appropriate OCR software is a critical decision. Opt for established and reputable OCR solutions with advanced recognition capabilities. Some popular OCR software options include Adobe Acrobat, ABBYY FineReader, and Tesseract. Consider the software’s ability to handle different languages and fonts, as this can impact accuracy when dealing with multilingual documents.

Perform Pre-Processing on Images

To further enhance OCR accuracy, consider applying pre-processing techniques to the scanned images. This can include tasks such as:

  1. Deskewing: Correcting any skew or rotation in the scanned image.
  2. Despeckling: Removing noise and speckles from the image.
  3. Contrast Enhancement: Adjusting the image’s contrast to make text more legible.
  4. Thresholding: Converting grayscale images into binary images for better character recognition.

By applying these techniques, you can significantly improve OCR results, especially for documents with poor image quality.

Train OCR for Specific Fonts and Languages

OCR software often comes with default settings for recognizing common fonts and languages. However, for specialized documents or less commonly used fonts, it’s advisable to train the OCR software. This involves providing sample text in the target font or language to help the software adapt and recognize characters accurately.

Proofread and Correct Errors

Even with the best practices in place, OCR errors can still occur. It’s essential to proofread and correct any errors in the converted text manually. Regularly review the OCR output and compare it to the original document to ensure accuracy. This step is particularly crucial for critical documents.


Optimizing OCR accuracy in document scanning is essential for efficient document management and data extraction. By following these best practices, you can ensure that your OCR software delivers reliable and accurate results, saving you time and effort in the long run. Remember that while OCR technology continues to improve, it’s always a good idea to review the converted text for any potential errors.

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