Image mosaicking using SURF features of line segments

Zhanlong Yang; Dinggang Shen; Pew Thian Yap

doi:10.1371/journal.pone.0173627

Image mosaicking using SURF features of line segments

Zhanlong Yang, Dinggang Shen, Pew Thian Yap

Research output: Contribution to journal › Article › peer-review

22 Citations (Scopus)

Abstract

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.

Original language	English
Article number	e0173627
Journal	PloS one
Volume	12
Issue number	3
DOIs	https://doi.org/10.1371/journal.pone.0173627
Publication status	Published - 2017 Mar

Bibliographical note

Publisher Copyright:
© 2017 Yang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

ASJC Scopus subject areas

General

Access to Document

10.1371/journal.pone.0173627

Cite this

@article{754e422aee0348c8b50a99e2ae5185b1,

title = "Image mosaicking using SURF features of line segments",

abstract = "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.",

author = "Zhanlong Yang and Dinggang Shen and Yap, {Pew Thian}",

note = "Publisher Copyright: {\textcopyright} 2017 Yang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.",

year = "2017",

month = mar,

doi = "10.1371/journal.pone.0173627",

language = "English",

volume = "12",

journal = "PloS one",

issn = "1932-6203",

publisher = "Public Library of Science",

number = "3",

}

TY - JOUR

T1 - Image mosaicking using SURF features of line segments

AU - Yang, Zhanlong

AU - Shen, Dinggang

AU - Yap, Pew Thian

N1 - Publisher Copyright: © 2017 Yang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

PY - 2017/3

Y1 - 2017/3

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=85015361883&partnerID=8YFLogxK

U2 - 10.1371/journal.pone.0173627

DO - 10.1371/journal.pone.0173627

M3 - Article

C2 - 28296919

AN - SCOPUS:85015361883

SN - 1932-6203

VL - 12

JO - PloS one

JF - PloS one

IS - 3

M1 - e0173627

ER -

Image mosaicking using SURF features of line segments

Abstract

Bibliographical note

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this