目的 引入K-means聚类算法量化评估印张与客户样网点面积率差异,运用非线性拟合算法确定C/M/Y/K四色通道优化调整参数,实现印刷返单色彩精准补偿还原。方法 调用扫描仪与机台印刷ICC配置文件,将扫描的RGB文件转换为与印前分色标准一致的CMYK文件;引入K-means聚类算法模型,对印张与客户样的C/M/Y/K分色文件进行高精度比对;用非线性拟合算法确定四色通道优化调整节点及参数;在Photoshop中对C/M/Y/K 4个颜色通道进行“曲线”调整。结果 动态补偿机制有效校正印张偏蓝、偏深缺陷,同步优化四原色、二次叠印色和三色叠印灰平衡色,补偿修正后印张色差∆E00稳定控制在2.5以内。结论 该数据驱动补偿方法效率远超传统人工调整,具有完全可复制的标准化特性,为印刷生产数字化升级提供关键技术支撑。
Abstract
The work aims to introduce the K-means clustering algorithm to quantitatively assess the difference in dot area rate distribution between printed sheets and customer samples, utilize nonlinear fitting algorithms to determine the optimization adjustment parameters for theC/M/Y/K four-color channels, and achieve precise color compensation and restoration for reprinted prints. A scanner and machine printing ICC profile was used to convert scanned RGB files into CMYK files consistent with pre-press color separation standards. The K-means clustering algorithm model was introduced to conduct high-precision comparisons of the C/M/Y/K color-separated files of printed sheets and customer samples. Nonlinear fitting algorithms were used to determine the optimization adjustment nodes and parameters for the four-color channels. "Curve" adjustments were conducted for the C/M/Y/K four color channels in Photoshop. The dynamic compensation mechanism effectively corrected the defects of printed sheets being too blue or too dark, synchronously optimized the four primary colors, secondary overprint colors, and three-color overprint gray balance colors, and stabilized the color difference ΔE2000 of the compensated and corrected printed sheets within 2.5. This data-driven compensation method significantly outperforms traditional manual adjustments in efficiency, possesses fully replicable standardized characteristics, and provides key technical support for the digital upgrading of printing production.
关键词
K-means聚类算法 /
印刷返单追样 /
色彩补偿 /
色彩管理
Key words
K-means clustering algorithm /
printing reorder sample-matching /
color compensation /
color management
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基金
广东省普通高校科研新一代电子信息（半导体）重点领域项目（2025ZDZX1086）
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