2维条码目前已广泛应用于各个领域，2维条码的编码过程中有一个重要步骤称为掩模调制，其目的是为了限制生成图像各区域的平均灰度，以提高码字的易印制、易识别能力。但现有的掩模方法大多基于感性，掩模模式有限并缺乏规范的方法支持及客观的评估手段，难以在各种应用条件下取得最佳效果。本文的研究目的是对能够对2维条码的掩模进行一种客观的数学上的评估。本文结合作者自行提出的一种可承载不确定容量信息的连续型2维条码，从统计分布模型角度对掩模技术进行研究，通过一种归于正态分布的数学评估模型，最终引导出一种比传统方法更为客观、规范、可最优化的掩模方法，该技术还可以应用于QR码等2维编码规则中。

2D barcodes are two-dimensional graphical patterns that encode information. During encoding there is an important stage named mask modulation the purpose of which is to limit the average gray level of each area of resulting image and to make it suitable for printing and recognition. Since the traditional schemes are mostly based on perceptual template pattern selection and lack formal method and objective evaluation is based on quantitative analysis, resulting non-optimal selection during application. Our task is to objectively and mathematically evaluate the mask modulation. In this paper, based on a 2-dimensional continuous matrix bar code with uncertain capacity, we introduce an evaluation method of graphical patterns based on mathematic statistical model. This evaluation is more impersonal and optimal than the traditional method.