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

Department of Brain and Cognitive Engineering

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

17 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

ASJC Scopus subject areas

Biochemistry, Genetics and Molecular Biology(all)
Agricultural and Biological Sciences(all)
General

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10.1371/journal.pone.0173627

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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 = "Funding Information: This work was partially supported by the National Natural Science Foundation of China (No. 61540047), the Northwestern Polytechnical University Foundation for Fundamental Research (NPU-FFRJC201226), and NIH grants (NS093842, EB006733, EB008374, and EB009634). 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.",

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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.

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Image mosaicking using SURF features of line segments

Abstract

ASJC Scopus subject areas

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