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OCR reads the pixels in an image, not the paper itself. A phone photo that looks readable to you can still give OCR weak or ambiguous character shapes because of blur, low detail, poor contrast, uneven lighting, rotation, or small, colored, or dense text. Those are known accuracy factors—not proof that any one caused a particular failed result.
Why a document photo can confuse OCR
A clean scan tends to present text as a flat, evenly lit image. A handheld photo may capture the same page with less detail or less consistent visual contrast. When letters are hard to distinguish in the image, recognition becomes less reliable.
Microsoft identifies scan quality, resolution, contrast, lighting, rotation, and text attributes such as size, color, and density as factors that can affect OCR accuracy. The service and document matter too: a particular error cannot be attributed to one factor without examining the image and the OCR system that processed it. Microsoft Learn’s OCR guidance recommends testing representative samples and deciding how uncertain results should be handled.
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- Check the image itself. Zoom in and confirm the text is legible. Look for blur or missing detail, weak contrast, uneven light, a rotated page, and text that is unusually small, colored, or densely packed.
- Retake one clear photo of the document. Microsoft recommends one clear photo or a high-quality scan per document. Keep the page and text legible in the resulting image rather than relying on the OCR service to repair a poor capture. Microsoft’s Document Intelligence Read guidance gives this input advice.
- Keep the original file detail. If you submit a supported file to Amazon Textract, AWS advises against converting or downsampling it first. AWS recommends high-quality input, ideally at least 150 DPI; this is an ideal-input recommendation, not a universal pass/fail threshold for phone photos. AWS Textract best practices list JPEG, PNG, PDF, and TIFF as supported formats.
- Review the extracted text where mistakes matter. Compare OCR output against the document, especially for consequential decisions, and send uncertain cases to a person for review.
What OCR resolution and confidence numbers mean
Published limits belong to particular products and contexts. They are not interchangeable specifications for every OCR app or camera image.
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| Service and context | Published figure | How to interpret it |
|---|---|---|
| Amazon Textract input guidance | Ideally at least 150 DPI | AWS recommendation for high-quality input, not a universal minimum. AWS best practices. |
| Amazon Textract character detection | Minimum character height of 15 pixels | A service-specific minimum in AWS quota documentation, not a general OCR rule. AWS Textract quotas. |
| Microsoft Document Intelligence Read | Minimum text height of 12 pixels for a 1024 × 768 image | Applies to the stated Document Intelligence Read context; do not merge it with another product’s limits. The same guidance lists image dimensions of 50–10,000 pixels. Microsoft Read model guidance. |
| Microsoft OCR confidence example | 0.80 | An example cutoff for routing results to straight-through processing or human review, not a prescribed threshold. Microsoft OCR characteristics and limitations. |
| Amazon Textract confidence | 0–100 | AWS says to choose how confidence informs review based on the use case. Its examples include an archival threshold as low as 50% and 90% or higher for financial decisions; these are AWS examples, not universal settings. AWS Textract best practices. |
Confidence is a signal for deciding what to check, not proof that extracted text is correct. Microsoft recommends evaluating representative documents to set review levels. For sensitive or consequential use, validate the text and choose thresholds for the specific service and task.
When a scanner is worth considering
If you digitize paper frequently, a document scanner is one option for producing high-quality scans. The available guidance supports using clear photos or high-quality scans, but does not establish that a scanner is always better than a careful phone capture, or that buying one is necessary. For occasional pages, first improve the capture and preserve the image detail.
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Check service and language support
Image quality is only one part of compatibility. For example, the AWS documentation lists English, French, German, Italian, Portuguese, and Spanish for Textract text detection and says its handwriting recognition is English-only. Microsoft’s OCR characteristics guidance says its current version supports cursive-style handwriting only for English. Supported languages and limits can change, so check the current documentation for the exact product, model, and endpoint you use.
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