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September 5, 2025Technology audit and production reservesOpen Access

Development of a method for using color in machine-readable optical codes to increase the information capacity

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Authors

OKOleksandr KozyraAFA. FechanVDVladyslav Daliavskyi

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Overview

This method improves information capacity in QR codes using color spaces, suggesting compatibility with existing codes.

Key Points

  • Using color in qr codes led to a significant increase in information capacity, enabling 16-color versions.
  • The oklch color space achieved 60% successful reads of complex images, outperforming other color models.
  • Algorithms were developed for efficient encoding and decoding, addressing issues in image quality and lighting.
  • This innovation allows for new standards in machine-readable codes while maintaining backward compatibility.

Cite This Study

Kozyra et al. (2025) studied this question.

synapsesocial.com/papers/68bb49d26d6d5674bccffed1https://doi.org/10.15587/2706-5448.2025.332931
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1The Application of Back-Compatible Color QR Codes to Colorimetric Sensors2024 · 1 citations
  2. 2Optimized Data Management with Color Multiplexing in QR Codes2024
  3. 3QRGB+: Advanced QR Code Generator with RGB Color Method in Python to Expand Data Capacity2024
  4. 4QRGB: App for QR Code Generation (3-in-1 Method), Additive Color Generation Method (RGB), Using Python Programming Code, to Increase Accumulated Information Density2024
  5. 5QRGB: App for QR Code Generation (3-in-1 Method), Additive Color Generation Method (RGB), Using Python Programming Code, to Increase Accumulated Information Density2024 · 4 citations