Publication detail

Search for Similarity Transformation Between Image Point Clouds Using Geometric Algebra for Conics

DEREVIANKO, A. LOUČKA, P.

Original Title

Search for Similarity Transformation Between Image Point Clouds Using Geometric Algebra for Conics

Type

conference paper

Language

English

Original Abstract

We introduce a novel way of searching for the similarity transformation of 2D point clouds using Geometric Algebra for Conics (GAC). In our approach, we do not represent the image objects by their contour but, instead, by the ellipse fitted into the contour points. Such representation makes the consequent similarity search fast and memory-saving. Examples of application on the real object images are also included.

Keywords

Geometric algebra; Clifford algebra; Transformation; Point cloud; Image processing

Authors

DEREVIANKO, A.; LOUČKA, P.

Released

2. 4. 2022

Publisher

SPRINGER INTERNATIONAL PUBLISHING AG

Location

CHAM

ISBN

978-3-030-98259-1

Book

Modelling and Simulation for Autonomous Systems

Pages from

215

Pages to

226

Pages count

12

URL

https://link.springer.com/chapter/10.1007/978-3-030-98260-7_13#chapter-info

BibTex

@inproceedings{BUT177873,
  author="Anna {Derevianko} and Pavel {Loučka}",
  title="Search for Similarity Transformation Between Image Point Clouds Using Geometric Algebra for Conics",
  booktitle="Modelling and Simulation for Autonomous Systems",
  year="2022",
  volume="13207",
  pages="215--226",
  publisher="SPRINGER INTERNATIONAL PUBLISHING AG",
  address="CHAM",
  doi="10.1007/978-3-030-98260-7\{_}13",
  isbn="978-3-030-98259-1",
  url="https://link.springer.com/chapter/10.1007/978-3-030-98260-7_13#chapter-info"
}