Automatic SRAF printing detection based on contour extraction

Liang Cao; Jie Zhang; Wenchao Jiang; Jiechang Hou; Dongqing Zhang; Wei-long Wang

doi:10.1117/12.2280186

16 October 2017 Automatic SRAF printing detection based on contour extraction

Liang Cao, Jie Zhang, Wenchao Jiang, Jiechang Hou, Dongqing Zhang, Wei-long Wang

Proceedings Volume 10451, Photomask Technology 2017; 104511J (2017) https://doi.org/10.1117/12.2280186
Event: SPIE Photomask Technology and EUV Lithography, 2017, Monterey, California, United States

Abstract

Sub-Resolution Assist Feature (SRAF) printing detection is critical during SRAF model building. Currently, SRAF printing detection on silicon wafer is mainly through human judgement on CDSEM images, which is inefficient and error prone. Therefore, a robust automatic SRAF printing classification mechanism is essential to improve detection accuracy and efficiency. This paper presents a method of classifying SRAF printing based on a database-independent contour extraction algorithm. By size calculation on extracted contour SRAF feature printing classification can be made automatically. This flow has been demonstrated to be able to correctly classify SRAF printing with consistent performance thus avoid the subjectivity and inconsistency in human judgement.

Citation Download Citation

Liang Cao, Jie Zhang, Wenchao Jiang, Jiechang Hou, Dongqing Zhang, and Wei-long Wang "Automatic SRAF printing detection based on contour extraction", Proc. SPIE 10451, Photomask Technology 2017, 104511J (16 October 2017); https://doi.org/10.1117/12.2280186

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