Feature identification of non-stochastic surfaces with non-subsampled contourlet transform

LinFu Li; JianJun Chen; Hong Chen; ChuanBo Zhang

doi:10.1117/12.2575186

10 October 2020 Feature identification of non-stochastic surfaces with non-subsampled contourlet transform

LinFu Li, JianJun Chen, Hong Chen, ChuanBo Zhang

Author Affiliations +

Proceedings Volume 11552, Optical Metrology and Inspection for Industrial Applications VII; 115521N (2020) https://doi.org/10.1117/12.2575186
Event: SPIE/COS Photonics Asia, 2020, Online Only

Conference Poster

Abstract

Surface defects and texture features have a significant effect on the opticalcal properties of advanced optical components. However, most precision optical components have non-stochastic surfaces, so the current defect identification algorithm needs to be further improved to meet the quality inspection requirements for non-stochastic surfaces. In this paper, the scheme of non-subsampled contourlet transform is applied to identify feature of non-stochastic surfaces. A concrete analysis of sparse representation and feature identification about the non-subsampled contourlet transform were presented. The effectiveness of the method is proved by simulation results and experimental examples.

Conference Presentation

Citation Download Citation

LinFu Li, JianJun Chen, Hong Chen, and ChuanBo Zhang "Feature identification of non-stochastic surfaces with non-subsampled contourlet transform", Proc. SPIE 11552, Optical Metrology and Inspection for Industrial Applications VII, 115521N (10 October 2020); https://doi.org/10.1117/12.2575186

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