The Experts below are selected from a list of 6 Experts worldwide ranked by ideXlab platform

Jian Wei Wan - One of the best experts on this subject based on the ideXlab platform.

  • Affine Image Registration Based on Geometric Inference
    Applied Mechanics and Materials, 2013
    Co-Authors: Xing Wei Yan, Jun Zhang, Jian Wei Wan
    Abstract:

    Image registration is widely used in applications for mapping one image to another. As it is often formulated as a Point matching problem, in this paper, a novel method, called the Geometric Inference (GI) algorithm, is proposed for feature Point based image registration. Firstly, according to affine distance invariant, the global geometric relationship between collinear correspondences is deduced and used for collinear Point matching. Secondly, utilizing affine area invariant, geometric relationship between Noncollinear correspondences is inferred and used for Noncollinear Point matching. Finally, the best affine transformation can be discovered from the correspondences composed of the collinear and Noncollinear corresponding Point pairs. Experiments on synthesized and real data demonstrate that GI is well-adapt to image registration as it is fast and robust to missing Points, outliers, and noise.

Xing Wei Yan - One of the best experts on this subject based on the ideXlab platform.

  • Affine Image Registration Based on Geometric Inference
    Applied Mechanics and Materials, 2013
    Co-Authors: Xing Wei Yan, Jun Zhang, Jian Wei Wan
    Abstract:

    Image registration is widely used in applications for mapping one image to another. As it is often formulated as a Point matching problem, in this paper, a novel method, called the Geometric Inference (GI) algorithm, is proposed for feature Point based image registration. Firstly, according to affine distance invariant, the global geometric relationship between collinear correspondences is deduced and used for collinear Point matching. Secondly, utilizing affine area invariant, geometric relationship between Noncollinear correspondences is inferred and used for Noncollinear Point matching. Finally, the best affine transformation can be discovered from the correspondences composed of the collinear and Noncollinear corresponding Point pairs. Experiments on synthesized and real data demonstrate that GI is well-adapt to image registration as it is fast and robust to missing Points, outliers, and noise.

Jun Zhang - One of the best experts on this subject based on the ideXlab platform.

  • Affine Image Registration Based on Geometric Inference
    Applied Mechanics and Materials, 2013
    Co-Authors: Xing Wei Yan, Jun Zhang, Jian Wei Wan
    Abstract:

    Image registration is widely used in applications for mapping one image to another. As it is often formulated as a Point matching problem, in this paper, a novel method, called the Geometric Inference (GI) algorithm, is proposed for feature Point based image registration. Firstly, according to affine distance invariant, the global geometric relationship between collinear correspondences is deduced and used for collinear Point matching. Secondly, utilizing affine area invariant, geometric relationship between Noncollinear correspondences is inferred and used for Noncollinear Point matching. Finally, the best affine transformation can be discovered from the correspondences composed of the collinear and Noncollinear corresponding Point pairs. Experiments on synthesized and real data demonstrate that GI is well-adapt to image registration as it is fast and robust to missing Points, outliers, and noise.

Rudnev Misha - One of the best experts on this subject based on the ideXlab platform.

  • Geometric incidence type results in the plane over the prime field
    Banff International Research Station for Mathematical Innovation and Discovery, 2018
    Co-Authors: Rudnev Misha
    Abstract:

    The plan is to review some better or less known results about incidences of sufficiently small Noncollinear Point sets with straight lines. The two best known and in some sense sharp results are the theorem on distinct directions proved in the 90s by T. Szonyi and the recent Szemeredi–Trotter type incidence theorem by S. Stevens and F. de Zeeuw. Can further progress be expected to come reasonably soon?Non UBCUnreviewedAuthor affiliation: University of BristolFacult