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

Haowei Zhang; Zhihe Zhang; Zhaoyan Yan; Yan Li

doi:10.1117/12.2680171

27 June 2023 Fast line segment matching based on point-line affine invariants and pairwise constraints

Haowei Zhang, Zhihe Zhang, Zhaoyan Yan, Yan Li

Proceedings Volume 12705, Fourteenth International Conference on Graphics and Image Processing (ICGIP 2022); 127052W (2023) https://doi.org/10.1117/12.2680171
Event: Fourteenth International Conference on Graphics and Image Processing (ICGIP 2022), 2022, Nanjing, China

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.

Citation Download Citation

Haowei Zhang, Zhihe Zhang, Zhaoyan Yan, and Yan Li "Fast line segment matching based on point-line affine invariants and pairwise constraints", Proc. SPIE 12705, Fourteenth International Conference on Graphics and Image Processing (ICGIP 2022), 127052W (27 June 2023); https://doi.org/10.1117/12.2680171

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KEYWORDS

Feature extraction

Tunable filters

Light sources and illumination

Image enhancement

Image processing

Matrices

Visualization

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