Title :
Self-Inspection for Defect Detection in Photomask Image
Author :
Choi, Jihee ; Jeong, Hong
Author_Institution :
Dept. of EEE, Pohang Univ. of Sci. & Technol., Pohang
Abstract :
This paper describes a new method for the process of extracting photomask defects using a single optical photomask image which is not aligned. The lines of a photomask picture are not parallel with the pixel grid, and so there is always a angle of error. Only one sample image which contains defects was used in our tests. The algorithm is effective because we only need one sample photomask image. It not only extracts general patterns of photomask defects but also relatively small and discontinuous patterns.
Keywords :
feature extraction; masks; optical photomask image; photomask defect detection; self-inspection; Data mining; Glass; Image segmentation; Information technology; Inspection; Manufacturing processes; Photonic integrated circuits; Semiconductor device manufacture; Testing; Voting; defect detection; photomask; rotation; self-inspection;
Conference_Titel :
Convergence and Hybrid Information Technology, 2008. ICCIT '08. Third International Conference on
Conference_Location :
Busan
Print_ISBN :
978-0-7695-3407-7
DOI :
10.1109/ICCIT.2008.217