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Image mosaicking using SURF features of line segments

In this paper, we present a novel image mosaicking method that is based on Speeded-Up Robust Features (SURF) of line segments, aiming to achieve robustness to incident scaling, rotation, change in illumination, and significant affine distortion between images in a panoramic series. Our method involv...

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Detalles Bibliográficos
Autores principales: Yang, Zhanlong, Shen, Dinggang, Yap, Pew-Thian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5351852/
https://www.ncbi.nlm.nih.gov/pubmed/28296919
http://dx.doi.org/10.1371/journal.pone.0173627
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author Yang, Zhanlong
Shen, Dinggang
Yap, Pew-Thian
author_facet Yang, Zhanlong
Shen, Dinggang
Yap, Pew-Thian
author_sort Yang, Zhanlong
collection PubMed
description In this paper, we present a novel image mosaicking method that is based on Speeded-Up Robust Features (SURF) of line segments, aiming to achieve robustness to incident scaling, rotation, change in illumination, and significant affine distortion between images in a panoramic series. Our method involves 1) using a SURF detection operator to locate feature points; 2) rough matching using SURF features of directed line segments constructed via the feature points; and 3) eliminating incorrectly matched pairs using RANSAC (RANdom SAmple Consensus). Experimental results confirm that our method results in high-quality panoramic mosaics that are superior to state-of-the-art methods.
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spelling pubmed-53518522017-04-06 Image mosaicking using SURF features of line segments Yang, Zhanlong Shen, Dinggang Yap, Pew-Thian PLoS One Research Article In this paper, we present a novel image mosaicking method that is based on Speeded-Up Robust Features (SURF) of line segments, aiming to achieve robustness to incident scaling, rotation, change in illumination, and significant affine distortion between images in a panoramic series. Our method involves 1) using a SURF detection operator to locate feature points; 2) rough matching using SURF features of directed line segments constructed via the feature points; and 3) eliminating incorrectly matched pairs using RANSAC (RANdom SAmple Consensus). Experimental results confirm that our method results in high-quality panoramic mosaics that are superior to state-of-the-art methods. Public Library of Science 2017-03-15 /pmc/articles/PMC5351852/ /pubmed/28296919 http://dx.doi.org/10.1371/journal.pone.0173627 Text en © 2017 Yang et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Yang, Zhanlong
Shen, Dinggang
Yap, Pew-Thian
Image mosaicking using SURF features of line segments
title Image mosaicking using SURF features of line segments
title_full Image mosaicking using SURF features of line segments
title_fullStr Image mosaicking using SURF features of line segments
title_full_unstemmed Image mosaicking using SURF features of line segments
title_short Image mosaicking using SURF features of line segments
title_sort image mosaicking using surf features of line segments
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5351852/
https://www.ncbi.nlm.nih.gov/pubmed/28296919
http://dx.doi.org/10.1371/journal.pone.0173627
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