Study on improved scale Invariant Feature Transform matching algorithm

Yang You-liang; Weili Liu; Lan Zhang

doi:10.1109/paccs.2010.5626923

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Study on improved scale Invariant Feature Transform matching algorithm

Yang You-liang Weili Liu Lan Zhang

Year: 2010 Pages: 398-401

DOI: 10.1109/paccs.2010.5626923

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Abstract

False matching feature points are caused by Scale Invariant Feature Transform (SIFT) which just considers the local feature information. In order to improve the precision of matching feature points, this paper proposes a method that combines the SIFT matching, epipolar restrict and regional matching. It is used to eliminate the superfluous error matching points to improve matching accuracy.

Keywords:

Scale-invariant feature transform Matching (statistics) Epipolar geometry Feature matching Artificial intelligence Pattern recognition (psychology) Feature (linguistics) Computer science Image matching Invariant (physics) Feature extraction Computer vision Blossom algorithm Optimal matching Algorithm Mathematics Image (mathematics) Statistics

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Topics

Advanced Image and Video Retrieval Techniques

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Advanced Measurement and Detection Methods

Physical Sciences → Engineering → Electrical and Electronic Engineering

Robotics and Sensor-Based Localization

Physical Sciences → Engineering → Aerospace Engineering

Study on improved scale Invariant Feature Transform matching algorithm

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