Image mosaicking using SURF features of line segments
Public Deposited- Creator
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Yang, Zhanlong
- Affiliation: School of Medicine, Biomedical Research Imaging Center
- Other Affiliation: School of Marine Science and Technology; Northwestern Polytechnical University
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Shen, Dinggang
- Affiliation: School of Medicine, Biomedical Research Imaging Center
- Other Affiliation: Department of Brain and Cognitive Engineering; Korea University
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Yap, Pew-Thian
- Affiliation: School of Medicine, Biomedical Research Imaging Center
- 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.
- Date of publication
- 2017
- Keyword
- DOI
- Identifier
- Onescience id: 5c44644744b468f2ceab06fcfda97ff9b3668a7c
- PMCID: PMC5351852
- PMID: 28296919
- Publisher DOI: https://doi.org/10.1371/journal.pone.0173627
- Resource type
- Article
- Rights statement
- In Copyright
- Journal title
- PloS One
- Journal volume
- 12
- Journal issue
- 3
- Page start
- e0173627
- Language
- English
- ISSN
- 1932-6203
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