吕明珠,吴学毅,成刚虎,岳喜娜.基于K-means聚类十字线的套印偏差检测方法研究[J].包装工程,2020,41(1):143-148.
LYU Ming-zhu,WU Xue-yi,CHENG Gang-hu,YUE Xi-na.Overprint Deviation Detection Method Based on K-means Clustering Cross Line[J].Packaging Engineering,2020,41(1):143-148. |
| 基于K-means聚类十字线的套印偏差检测方法研究 |
| Overprint Deviation Detection Method Based on K-means Clustering Cross Line |
| 投稿时间：2019-06-12 修订日期：2020-01-10 |
| DOI：10.19554/j.cnki.1001-3563.2020.01.022 |
| 中文关键词: K-means聚类 印刷品 十字线 套印偏差 |
| 英文关键词: K-means clustering print cross line overprint deviation |
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| 中文摘要: |
| 目的 研究并改进基于十字线套准标识符的印刷品套印偏差检测算法，以提升偏差量检测精度。方法 使用K-means聚类算法对分色后得到的C，M，Y，K图像分别进行聚类处理，然后分割图像并提取出各色前景像素，进而使用C，M，Y图像中的前景十字线分别减去K图像中的十字线，以消除四色重叠区域的干扰，最后提取十字线中心并计算偏差量。结果 使用15幅印刷品图像样张进行实验，改进的基于K-means聚类十字线的套印偏差检测算法的检测结果，比大津法更接近人工测量值，误差在±0.04 mm以内。结论 基于K-means聚类的十字线分割法对前景十字线的提取，较大津法抗叠印干扰性更强。 |
| 英文摘要: |
| The paper aims to research and improve the printing overprint deviation detection algorithm based on cross line alignment identifier to improve the accuracy of the deviation detection. Firstly, the K-means clustering algorithm was used to cluster the C, M, Y and K images obtained after color separation. Secondly, the fourimage arerespective segmented and the each foreground pixels were extracted. Then the foreground cross lines in C, M and Y images were respectively subtracted from the cross lines in K images to eliminate the interference of four-color overlapping regions. Finally, the center of the cross line was extracted and the deviation was calculated. Experiments on 15 printed image samples showed that results of the improved overprint deviation detection algorithm based K-means clustering cross line was closer to the manual measurement results than Otsu method, and the error was within (±0.04 mm). The cross-line segmentation method based on K-means clustering is more resistant to overlay interference than Otsu method in foreground cross-line extraction. |
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