JOURNAL ARTICLE

Fast line segment matching based on point-line affine invariants and pairwise constraints

Abstract

In this paper we propose a method about line segment matching based on point-line invariants. We use ORB and EDlines, two efficient and stable methods, to extract point and line features respectively. Then we introduce the implementation details of our matching algorithm. It includes affine invariance of the ratio of the distance from two coplanar points to the line and pairwise constraint of the geometric relationship between two lines. In order to eliminate mismatches, we use a series of methods to optimize the result of our algorithm. We set up a scoring mechanism for candidate matches and the final matches will be given by evaluating the voting matrix. Its performance is evaluated by extensive experiments. The results show that our proposed method outperforms the mainstream methods, and are robust to rotation, scale, blur and other transformations.

Keywords:
Affine transformation Line segment Pairwise comparison Line (geometry) Matching (statistics) Computer science Rotation (mathematics) Algorithm Point (geometry) Point set registration Artificial intelligence Mathematics Geometry

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Topics

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

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