QR Code Validator

Upload a QR code image to analyze its version, error correction level, mask pattern, encoding mode, and quality.

Drop a QR code image here

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Upload a QR code image to see analysis results

Decoded Data

QR Code Properties

Quality Grade

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How to Use This Tool

  1. 1
    Upload the QR code image

    Select and upload the QR code image file (PNG or JPEG) that you want to validate; higher-resolution images yield more detailed analysis.

  2. 2
    Run the validation analysis

    The tool decodes the symbol and evaluates key quality parameters including version, error-correction level, module size uniformity, and quiet zone compliance.

  3. 3
    Review the quality report

    Examine the detailed report, noting any warnings about marginal contrast, violated quiet zones, or damaged modules, and use the recommendations to improve the design or print process.

Frequently Asked Questions

What parameters does QR code validation check?

A comprehensive validator evaluates both structural and quality parameters. Structural checks confirm that the finder patterns, timing patterns, format information, and version information (for Version 7 and above) are correctly encoded according to ISO/IEC 18004. Quality checks assess symbol contrast (the reflectance difference between dark and light modules), modulation (uniformity of module reflectance), axial non-uniformity (whether the code is stretched or compressed on one axis), and quiet zone adequacy. ISO/IEC 15415 defines a graded quality metric from A (best) to F (fail) for two-dimensional barcodes including QR codes.

What is a good quality grade for a QR code?

ISO/IEC 15415 grades QR code quality on a scale from 4.0 (Grade A) down to 0 (Grade F). For retail and consumer applications, a minimum grade of 1.5 (Grade C) is typically acceptable. Mission-critical applications such as medical device labelling, pharmaceutical track-and-trace, and financial services often require Grade 2.5 (B) or higher. The overall grade is the worst of the individual parameter grades, so a code that scores 4.0 on most parameters but 1.5 on contrast receives an overall grade of 1.5. Improving symbol contrast — usually by increasing ink density or using a darker ink on a lighter substrate — is the most common way to raise a marginal grade.

Why does a QR code scan correctly on my phone but fail validation?

Consumer smartphones implement aggressive image processing including adaptive thresholding, auto-exposure, and multi-frame averaging, which allows them to decode codes that fall below formal quality standards. Formal validation, by contrast, measures raw reflectance values and applies the strict ISO/IEC 15415 thresholds. A code may pass phone scanning but fail validation for quiet zone violations, marginal contrast, or axial non-uniformity that the phone's software compensates for. Codes intended for industrial scanners, kiosk readers, or printed packaging should meet formal quality grades rather than relying on smartphone tolerance.

How do logo overlays affect QR code quality?

A logo overlay reduces the effective data capacity by replacing modules with a non-standard pattern. The error-correction subsystem must recover the obscured data, so the overlay must not cover more codewords than the chosen error-correction level can restore. Level H can theoretically correct up to 30% of codewords, but practical guidance suggests limiting logo coverage to 15–20% to account for additional module damage from printing imperfections. A validator will flag overlays that exceed safe coverage limits and may be unable to grade standard quality parameters because the overlay disrupts reflectance measurements.

What causes module size non-uniformity and how is it fixed?

Module size non-uniformity typically results from inkjet dot gain (ink spreading beyond the intended module boundary), low print resolution relative to module size, or inconsistent substrate absorption. It is quantified as modulation in ISO/IEC 15415: low modulation means modules do not reliably reach target reflectance levels. Fixes include increasing print resolution, using a substrate with lower ink absorption, reducing ink density for dark modules (counterintuitively, oversaturated ink spreads more), or switching to laser printing which has tighter dot placement tolerances. For screen display, rendering modules at an integer number of pixels eliminates interpolation artefacts.