What Is OCR and How Does It Work
OCR is the technology that reads text from images. It works in three stages. First, image preprocessing: the tool adjusts contrast, straightens skewed pages, and removes background noise. Second, character recognition: the engine analyzes pixel patterns and matches them to known character shapes. Third, layout analysis: the engine determines reading order and reconstructs the text. Modern OCR engines achieve high accuracy on clean, clearly typed text. Handwriting, unusual fonts, and low-contrast scans reduce accuracy significantly.
Factors That Affect OCR Accuracy
Scan quality is the biggest factor. A clean 300 DPI scan produces near-perfect OCR results. A blurry 72 DPI scan produces unreliable output. Font type matters: standard typefaces are recognized accurately. Decorative fonts, handwriting, and very small type below 8pt are harder to recognize. Page skew: if the page runs at an angle, minor skew under 5 degrees is handled automatically. Severe skew or curved pages from phone camera photos can significantly reduce accuracy.
How to Get the Best OCR Results
Scan at 300 DPI or higher. This is the single most effective quality improvement. Most scanners default to 150-200 DPI, adequate for visual reading but below the threshold for reliable OCR. Use a flatbed scanner when possible. Phone camera photos introduce perspective distortion that reduces accuracy. Scan in grayscale or black and white rather than color. Color scans produce larger files without improving OCR accuracy.
How to Extract Text from a Scanned PDF - Step by Step
Open the ToolMint PDF to Text (OCR) tool. Upload your scanned PDF. The tool automatically detects whether the file requires OCR. For scanned files, OCR is applied automatically. Select the document language if prompted. Click Extract Text and wait for processing. Download the text output or copy it directly. Review the output for recognition errors — common mistakes include l being read as 1 and O being read as 0.
What to Do After Extracting Text
Extracted OCR text almost always contains some errors from lower-quality scans. A quick review for obvious substitutions is worth doing before using the text for important purposes. For plain text reuse — copying content into a new document or extracting figures for a spreadsheet — OCR output is usually accurate enough without extensive cleanup.