Peng Guifeng, Song Tao, Cao Songxiao, Zhou Bin, Jiang Qing
College of Metrology Measurement and Instrument, China Jiliang University, Hangzhou, 310018, China.
Sci Rep. 2024 Sep 4;14(1):20547. doi: 10.1038/s41598-024-71514-z.
The process of printing defect detection usually suffers from challenges such as inaccurate defect extraction and localization, caused by uneven illumination and complex textures. Moreover, image difference-based defect detection methods often result in numerous small-scale pseudo defects. To address these challenges, this paper proposes a comprehensive defect detection approach that integrates brightness correction and a two-stage defect detection strategy for self-adhesive printed materials. Concretely, a joint bilateral filter coupled with brightness correction corrects uneven brightness properly, meanwhile smoothing the grid-like texture in complex printed material images. Then, in the first detection stage, an image difference method based on a bright-dark difference template group is designed to effectively locate printing defects despite slight brightness fluctuations. Afterward, a discriminative method based on feature similarity is employed to filter out small-scale pseudo-defects in the second detection stage. The experimental results show that the improved difference method achieves an average precision of 99.1% in defect localization on five different printing pattern samples. Furthermore, the second stage reduces the false detection rate to under 0.5% while maintaining the low missed rate.
印刷缺陷检测过程通常面临诸多挑战，如因光照不均和纹理复杂导致缺陷提取和定位不准确。此外，基于图像差异的缺陷检测方法常常会产生大量小规模伪缺陷。为应对这些挑战，本文提出一种综合缺陷检测方法，该方法集成了亮度校正和针对自粘印刷材料的两阶段缺陷检测策略。具体而言，结合亮度校正的联合双边滤波器能恰当校正亮度不均，同时平滑复杂印刷材料图像中的网格状纹理。然后，在第一检测阶段，设计一种基于明暗差异模板组的图像差异方法，以有效定位印刷缺陷，即便存在轻微亮度波动。之后，在第二检测阶段采用基于特征相似性的判别方法来滤除小规模伪缺陷。实验结果表明，改进后的差异方法在对五个不同印刷图案样本进行缺陷定位时，平均精度达到99.1%。此外，第二阶段将误检率降低到0.5%以下，同时保持低漏检率。
