Zhan Hongwu, Shou Yuhao, Wen Lidu, Xu Fang, Zhang Libin
College of Mechanical Engineering, Zhejiang University of Technology, HangZhou, 310014, China.
Key Laboratory of Special Purpose Equipment and Advanced Processing Technology, Ministry of Education and Zhejiang Province, Zhejiang University of Technology, HangZhou, 310023, China.
Sci Rep. 2024 Oct 8;14(1):23449. doi: 10.1038/s41598-024-74179-w.
We propose an improved superpixel segmentation algorithm based on visual saliency and color entropy for online color detection in printed products. This method addresses the issues of low accuracy and slow speed in detecting color deviations in print quality control. The improved superpixel segmentation algorithm consists of three main steps: Firstly, simulating human visual perception to obtain visually salient regions of the image, thereby achieving region-based superpixel segmentation. Secondly, adaptively determining the superpixel size within the salient regions using color information entropy. Finally, the superpixel segmentation method is optimized using hue angle distance based on chromaticity, ultimately achieving a region-based adaptive superpixel segmentation algorithm. Color detection of printed products compares the color mean values of post-printing images under the same superpixel labels, outputting labels with color deviations to identify areas of color differences. The experimental results show that the improved superpixel algorithm introduces color phase distance with better segmentation accuracy, and combines it with human visual perception to better reproduce the color information of printed materials. Using the method described in this article for printing color quality inspection can reduce data computation, quickly detect and mark color difference areas, and provide the degree of color deviation.
我们提出了一种基于视觉显著性和颜色熵的改进超像素分割算法，用于印刷产品的在线颜色检测。该方法解决了印刷质量控制中颜色偏差检测精度低和速度慢的问题。改进的超像素分割算法主要包括三个步骤：首先，模拟人类视觉感知以获得图像的视觉显著区域，从而实现基于区域的超像素分割。其次，利用颜色信息熵自适应地确定显著区域内的超像素大小。最后，基于色度使用色相角距离对超像素分割方法进行优化，最终实现基于区域的自适应超像素分割算法。印刷产品的颜色检测通过比较相同超像素标签下印刷后图像的颜色均值，输出具有颜色偏差的标签以识别颜色差异区域。实验结果表明，改进的超像素算法引入颜色相位距离，分割精度更高，并将其与人类视觉感知相结合，能更好地再现印刷材料的颜色信息。使用本文所述方法进行印刷颜色质量检测可减少数据计算量，快速检测并标记色差区域，并提供颜色偏差程度。
