Open AccessImage mosaicking using SURF features of line segments
Author(s) -
Zhibin Yang,
Dinggang Shen,
Pew Thian Yap
Publication year - 2017
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0173627
Subject(s) - ransac , artificial intelligence , affine transformation , computer vision , robustness (evolution) , computer science , feature (linguistics) , pattern recognition (psychology) , image registration , rotation (mathematics) , line (geometry) , image (mathematics) , mathematics , geometry , biochemistry , chemistry , linguistics , philosophy , gene
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.