Publication | Open Access
Image mosaicking using SURF features of line segments
21
Citations
29
References
2017
Year
Geometric ModelingNovel ImageImage FormationImage AnalysisMachine VisionFeature DetectionEngineeringPattern RecognitionNatural SciencesImage MosaicingSurf FeaturesSurf Detection OperatorImage StitchingStructure From MotionEdge DetectionComputational GeometryComputer Vision
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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