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Wide-baseline matching based on line intersection features
Author(s): You Zhai; Xiwei Guo; Peng He; Dong Han
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Paper Abstract

To realize stable wide-baseline matching for structured scenes with low texture regions, a new matching method based on line intersection features (LIFS) is proposed, which combines the robustness of line feature and distinctiveness of keypoint’s descriptor. First, detect lines and compute line intersections. Second, line intersections from perspective projection of parallel lines or skew lines are filtered by parallel lines clustering and coplanar constraint which increases the stability and accuracy of line intersections. Third, local non maxima suppression is used to limit the intersections close to each other. Fourth, feature scales are computed for LIFS by simply utilizing the geometry distribution of intersections and endpoints of intersection lines. Finally, SURF descriptors are computed for LIFS in the computed scales and thus scale and rotation invariance is achieved. Experiment results show that compared with traditional matching method based on local features, the proposed method is more robust to image noise and illumination change. Besides, the proposed method has invariance to scale and rotation change and a certain degree of viewpoint change, providing an effective wide baseline matching method for images of structured scenes.

Paper Details

Date Published: 9 August 2018
PDF: 9 pages
Proc. SPIE 10806, Tenth International Conference on Digital Image Processing (ICDIP 2018), 1080607 (9 August 2018); doi: 10.1117/12.2502982
Show Author Affiliations
You Zhai, Shijiazhuang Branch of Army Engineering Univ. (China)
Xiwei Guo, Shijiazhuang Branch of Army Engineering Univ. (China)
Peng He, Shijiazhuang Branch of Army Engineering Univ. (China)
Dong Han, Shijiazhuang Branch of Army Engineering Univ. (China)


Published in SPIE Proceedings Vol. 10806:
Tenth International Conference on Digital Image Processing (ICDIP 2018)
Xudong Jiang; Jenq-Neng Hwang, Editor(s)

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