Abstract: Traditional paper defect detection algorithms have the problem of poor anti-interference ability, inaccurate positioning, complex computation. Considering this, a paper defect detection algorithm based on CB morphology and gray-code decomposition is presented. Firstly, the noise of the images containing paper defects is filtered by multi-scale CB morphology. Then, the filtered images are decomposed by gray-code decomposition. Finally, the edge of the important bitplane is detected by multi-structural elements CB morphology. The simulation results show that, this method is easily calculated, has a better anti-interference ability, and can accurately locate the paper defects.

Key words: Contour Bougie（CB） morphology, gray-code decomposition, paper defect detection

摘要： 传统纸病检测算法抗干扰能力差、定位不准确和运算复杂，针对该问题，提出了一种基于轮廓结构元素形态学和灰度码分解的纸病检测算法。首先，采用多尺度CB形态滤波算法对纸病图像进行滤波，再进行灰度码分解，最后运用多结构元素CB形态学提取重要位面图的边缘。仿真结果表明，该算法运算简单，具有较好的抗干扰能力，并能够较准确地定位纸病缺陷。

关键词: CB形态学, 灰度码分解, 纸病检测