Defect detection on images using multiple reference images: solving a binary labeling problem using graph-cuts algorithm

Janghee Lee; Suk In Yoo

doi:10.1117/1.JEI.21.3.033014

14 September 2012 Defect detection on images using multiple reference images: solving a binary labeling problem using graph-cuts algorithm

Janghee Lee, Suk In Yoo

Author Affiliations +

Journal of Electronic Imaging, Vol. 21, Issue 3, 033014 (September 2012). https://doi.org/10.1117/1.JEI.21.3.033014

Abstract

We present a new formulation to solve a defect detection problem on images using multiple reference images. The reference images are defect-free images obtained from the same position of other products. The defect detection problem is reformulated as a binary labeling problem, where each pixel is labeled with "one" if it contains a defect and with "zero" otherwise. The formulation of the energy function used for the labeling problem is defined. Then, the graph-cuts algorithm is used to obtain the optimal label set minimizing the energy function that becomes the defect detection result. The presented approaches are robust to noises taken from several sources, including image-taking, transmission process, environmental lighting, and pattern variation. It does not suffer from the alignment problem for the conventional comparison methods using references. These approaches are illustrated with real data sets, semiconductor wafer images collected by scanning electron microscope equipment, and compared to other defect detection approach.

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Janghee Lee and Suk In Yoo "Defect detection on images using multiple reference images: solving a binary labeling problem using graph-cuts algorithm," Journal of Electronic Imaging 21(3), 033014 (14 September 2012). https://doi.org/10.1117/1.JEI.21.3.033014

Published: 14 September 2012

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