JOURNAL ARTICLE

Rotation and scaling invariant feature lines for image matching

Abstract

Image matching has been one of the most fundamental issues computer vision over the decades. In this paper we propose a novel method based on making use of feature lines in order to achieve more robust image matching. The feature lines have the properties of rotation and scaling invariance, coined RIFLT(Rotation invariant feature line transform). Experimental results demonstrate the effectiveness and efficiency of the proposed method. Compare with the famous powerful algorithm 'Scale Invariant Feature Transform(SIFT)', the proposed method is more insensitive to noise. And for certain sequence of images, which contain clear lines, the proposed method is more efficiency. Using the feature lines obtained by our method, it is possible to matching two scene images with different rotation angles, scale and light distort.

Keywords:
Invariant (physics) Scaling Artificial intelligence Image matching Rotation (mathematics) Computer vision Pattern recognition (psychology) Computer science Matching (statistics) Feature matching Feature extraction Image (mathematics) Mathematics Geometry Statistics

Metrics

2
Cited By
0.26
FWCI (Field Weighted Citation Impact)
14
Refs
0.58
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Advanced Image and Video Retrieval Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Image Retrieval and Classification Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Robotics and Sensor-Based Localization
Physical Sciences →  Engineering →  Aerospace Engineering

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