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Robust and accurate pattern matching in fuzzy space for fiducial mark alignment

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Abstract

This paper presents a new pattern matching method for fiducial mark alignment in a fuzzy space. The membership functions of fuzzy sets are designed by distance transforms, and their levels are set in the fuzzy space for fast matching of a specific fiducial mark. After the fuzzification, a sub-pixel level translation is estimated by a fuzzy similarity measure and an interpolation using fuzzified model and target images. This paper also proposes a method of coarse-to-fine rotation estimation in sub-pixel level. Experiments show that the proposed fuzzy space pattern matching algorithm outperforms commercial pattern matching algorithms based on correlation or edge.

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Authors and Affiliations

  1. School of Information and Communication Engineering, INHA University, 253 Yonghyun-Dong, Nam-Gu, Incheon, 402-751, Korea

    Xuenan Cui, Hakil Kim & Eunsoo Park

  2. Electro-Mechanics, 314 Maetan3-Dong, Yeongtong-Gu, Suwon, 443-743, Korea

    Hyohoon Choi

Authors
  1. Xuenan Cui
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  2. Hakil Kim
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  3. Eunsoo Park
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  4. Hyohoon Choi
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Correspondence to Xuenan Cui.

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Cui, X., Kim, H., Park, E. et al. Robust and accurate pattern matching in fuzzy space for fiducial mark alignment. Machine Vision and Applications 24, 447–459 (2013). https://doi.org/10.1007/s00138-012-0433-5

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  • DOI: https://doi.org/10.1007/s00138-012-0433-5

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