Image Quality Control Analysis
Upload reference and sample images to begin quality control analysis
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Professional Color & Pattern Analysis
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Test6.pngUpload reference and sample images to begin quality control analysis
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Details shown on the generated report.
Select preprocessing technique for image alignment before comparison analysis.
Define the shape and dimensions of the analysis region.
Configure analysis implementation for Single Image Mode.
Select sections to include in the Single Image report.
Select which metric determines the Color Score, Pass/Conditional/Fail decision, and report cover display.
Define pass/fail criteria for color difference.
Define color thresholds for the Color Similarity Index.
Define component-level thresholds for Lab* quality assessment.
Configure how analysis points are selected for Color Analysis.
Select which metric determines the Pattern Score on the report cover and UI.
Define similarity scores (0-100%) for pattern analysis.
Controls how aggressively the Gradient and Phase methods highlight problematic regions. Higher values detect more subtle differences; lower values show only obvious defects.
Select the primary illuminant used for the entire report.
Enable illuminants for comparative color testing (displayed in Color Unit only).
Select components for the Color Unit section.
Select which pattern algorithms to run and include.
This website is currently under development.
You can view the results through the ready-made samples from the Samples section on the left side of the screen.
Or, to test new samples, download the source code (Python) and test it directly in the Google Colab environment.
To obtain full results, these logos must be added to Google Colab with the same filenames.
Copy the code and paste it into the Google Colab environment.
The complete technical documentation is available in PDF format.
Available in English and Turkish