16 October 2017 Automatic SRAF printing detection based on contour extraction
Author Affiliations +
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.
© (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Liang Cao, Liang Cao, Jie Zhang, Jie Zhang, Wenchao Jiang, Wenchao Jiang, Jiechang Hou, Jiechang Hou, Dongqing Zhang, Dongqing Zhang, Wei-long Wang, Wei-long Wang, } "Automatic SRAF printing detection based on contour extraction", Proc. SPIE 10451, Photomask Technology, 104511J (16 October 2017); doi: 10.1117/12.2280186; https://doi.org/10.1117/12.2280186


Automatic ship target classification based on aerial images
Proceedings of SPIE (January 27 2009)
Gabor wavelets for texture edge extraction
Proceedings of SPIE (August 16 1994)
Intraclass classification of tumor in brain MR images
Proceedings of SPIE (December 05 2001)

Back to Top