目的 纸张等薄片产品的批量计数在工业领域具有广泛应用，为此针对超薄叠层纸张机器视觉数量检测难题，提出一种全局周期约束与局部模式相关性度量相结合的鲁棒图像计数算法。方法 首先，沿层高方向提取1维图像剖面，利用频域梳状滤波器去噪，保留有用周期信号，借助波峰找寻算法确定候选纸张位置；然后，构造优化波峰模板，提出一种改进非零均值互相关（NCC）函数与原信号进行局部匹配。基于改进NCC函数的相关系数计算，能有效消除毛边、排列不齐、厚度和间隙变化等因素造成的虚检；最后，利用沿纸张方向的波形相似性和共线性，进一步消除干扰，根据不同剖面计数结果进行统计优化，输出最终测量数据。结果 针对多种类不同厚度的叠层纸张同时采用多种传统算法进行比较，本文算法对于影响纸张计数的常见干扰具有很强的抑制能力，其漏检率与误检率都显著低于其他传统算法。经统计，长期测量误差低于0.01%。结论 本文算法对单张厚度大于0.08 mm以上的纸张叠层有很高的检测精度且实时性强，适合自动化在线测量。

Objective Batch counting of thin sheet products such as paper has been widely applied in the industrial field. To solve the problem of machine vision quantity measurement for very thin paper stacks, a robust image counting algorithm based on global period constraint and local pattern correlation is presented. Method 1D profiles were extracted along the direction of stack height, and then denoised with Fourier spectrum analysis and a comb filter to preserve the useful period signal. Each candidate paper was located using a traditional peak finding algorithm. An optimal peak template was constructed, and an improved function of normalized cross-correlation was presented to calculate the correlation coefficient between the former template and the original signal by local matching. This approach helped reduce false detection from complex factors such as rugged edge, varying thickness and gap, and irregular arrangement. The collinear property and similar shape of signal wave were utilized to further suppress clutter, and the ultimate measure was obtained from optimal statistics of different profile counts. Result For comparison, the proposed method and several traditional algorithms were used together in counting experiments with different types of paper sheets with thickness varying from 0.08 mm to 0.23 mm. Our algorithm was verified to eliminate interference more effectively than other methods, and the missing and false alarm rates appeared comparatively low. Conclusion Our algorithm can achieve very high detection accuracy for paper sheets with thickness of more than 0.08 mm and has good real-time performance, which makes it suitable for in-line industrial applications with high accuracy requirement.