基于图像分析的CD-SEM显微视觉清晰度检测技术研究

Study on CD-SEM Microscopic Visual Clarity Detection Technology Based on Image Analysis

在集成电路制造业,对CD-SEM显微图像进行精确地清晰度检测是对关键层图案的特征尺寸CD(Critical Dimension)量测的基础。通过与目前常用的、具有代表性的多种清晰度评价方法进行实验验证分析和对比,提出一种基于小波变换和规则集合相结合的CD-SEM图像清晰度检测算法,首先利用小波变换分层提取图像的边缘特征,然后按照规则集合对边缘点进行不同边缘类型划分,最后计算图像模糊前后不同类型边缘点占总边缘点的比例来评价原始图像的清晰度。经过实验模拟验证和现场生产实践检验,该算法具有较高的计算精度和较强的鲁棒性、实时性和场景适应性。

In integrated circuit manufacturing, accurate sharpness detection of CD-SEM microscopy images is the basis for critical layer pattern of CD(Critical Dimension) measurements. In this paper, through the experimental verification and comparison with the commonly used and representative multiple resolution evaluation methods, a CD-SEM image sharpness detection algorithm based on wavelet transform and rule set is proposed. Firstly, the wavelet transform is used and the edge feature of the image is extracted, and then the edge type is divided according to the rule set. Finally, the ratio of different types of edge points to the total edge point before and after the image blur is calculated to evaluate the sharpness of the original image. After experimental simulation and field production practice test, the algorithm has high computational accuracy and strong robustness, real-time performance and scene adaptability.