纠错与数据完整性
Understanding Reed-Solomon error correction, EC levels L/M/Q/H, codeword structure, and how QR codes survive damage. Technical depth for developers and print professionals.
选择正确的纠错级别
Decision framework for selecting L, M, Q, or H based on environment, surface, expected damage, and data capacity needs.
Reed-Solomon编码：QR纠错背后的数学
Mathematical deep dive: Galois field GF(256), generator polynomials, syndrome calculation, and error location.
码字结构与交错
How data and EC codewords are organised into blocks and interleaved for damage distribution. Block structure per version and EC …
格式与版本信息中的BCH码和Golay码
How BCH(15,5) protects format data and Golay(18,6) protects version data. Encoding, detection, and correction explained.
QR Code能承受多大程度的损坏？
Real-world damage testing: scratches, tears, stains, fading, and partial obstruction. Visual examples of EC recovery.
纠错与徽标放置：可以覆盖多少？
The relationship between EC level and safe logo area. Guidelines for covering 10%, 15%, or 25% of the QR code.
数据容量与纠错的权衡
Quantifying the trade-off: how increasing EC level reduces capacity, and strategies for fitting more data at higher EC.
测试QR Code纠错：实践实验
How to test EC effectiveness: deliberate damage patterns, scanner comparison, and documenting the failure threshold.
Micro QR与rMQR中的纠错
How error correction differs in compact variants: Micro QR (L/M/Q) and rMQR (M/H only). Capacity implications.
结构化附加：跨多个QR Codes拆分数据
Using structured append mode to split large data across up to 16 QR symbols. Headers, reassembly, and practical limitations.
印刷质量与纠错：ISO 15415等级评定
ISO/IEC 15415 print quality grading for 2D symbols. Modulation, fixed pattern damage, and minimum grade requirements.
纠错失败时：调试无法读取的QR Codes
Systematic troubleshooting for QR codes that won't scan: contrast, quiet zone, size, encoding errors, and corruption.
恶劣环境下的纠错
EC strategies for outdoor, industrial, and medical environments: weather exposure, chemical resistance, and sterilisation cycles.
扫描仪如何处理错误：解码算法详解
Step-by-step decode process: pattern detection, format reading, data extraction, error correction, and mode interpretation.
QR纠错的未来：彩色QR及更多
Emerging techniques: colored modules for increased density, AI-assisted decoding, and next-generation 2D symbologies.