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A discrete approach for polygonal approximation of irregular noise contours

Authors :
Phuc Ngo
Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA)
Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)
Applying Discrete Algorithms to Genomics and Imagery (ADAGIO)
Department of Algorithms, Computation, Image and Geometry (LORIA - ALGO)
Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA)
Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)
Source :
CAIP 2019-Computer Analysis of Images and Patterns, CAIP 2019-Computer Analysis of Images and Patterns, Sep 2019, Salerno, Italy. pp.433-446, ⟨10.1007/978-3-030-29888-3_35⟩, Computer Analysis of Images and Patterns ISBN: 9783030298876, CAIP (1)
Publication Year :
2019
Publisher :
HAL CCSD, 2019.

Abstract

International audience; Polygonal approximation is often involved in many applications of computer vision, image processing and data compression. In this context, we are interested in digital curves extracted from contours of objects contained in digital images. In particular, we propose a fully discrete structure, based on the notion of blurred segments, to study the geometrical features on such curves and apply it in a process of polygonal approximation. The experimental results demonstrate the robustness of the proposed method to local variation and noise on the curve.

Details

Language :
English
ISBN :
978-3-030-29887-6
ISBNs :
9783030298876
Database :
OpenAIRE
Journal :
CAIP 2019-Computer Analysis of Images and Patterns, CAIP 2019-Computer Analysis of Images and Patterns, Sep 2019, Salerno, Italy. pp.433-446, ⟨10.1007/978-3-030-29888-3_35⟩, Computer Analysis of Images and Patterns ISBN: 9783030298876, CAIP (1)
Accession number :
edsair.doi.dedup.....09d566884586ce0d082a7bfbfb26cf01