• DocumentCode
    254557
  • Title

    A Robust Approach for Singular Point Extraction Based on Complex Polynomial Model

  • Author

    Jin Qi ; Suxing Liu

  • Author_Institution
    Electr. Eng. Dept., Univ. of Electron. Sci. & Technol. of China, Chengdu, China
  • fYear
    2014
  • fDate
    23-28 June 2014
  • Firstpage
    78
  • Lastpage
    83
  • Abstract
    This paper focuses on a general framework for singular point extraction from vector field. We design a new index of singular point based on complex polynomial model. We test our method in the publicly available benchmark dataset of the singular point detection competition (SPD2010). Our algorithm gets the best results and produces large margins compared to the top five algorithms which took part in the public competition. We also compare our algorithm with the state-of-the-art singular point detection algorithm (called "ZPM" method) with the benchmark. The performance of our method is much better than that of the state-of-the-art method.
  • Keywords
    feature extraction; object detection; polynomials; vectors; SPD2010 dataset; ZPM method; complex polynomial model; robust approach; singular point detection competition; singular point extraction; vector field; Computational modeling; Convergence; Indexes; Mathematical model; Polynomials; Vectors; Complex Polynomial model; Fingerprint Singular Point; Vector Field;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision and Pattern Recognition Workshops (CVPRW), 2014 IEEE Conference on
  • Conference_Location
    Columbus, OH
  • Type

    conf

  • DOI
    10.1109/CVPRW.2014.17
  • Filename
    6909962