When dealing with lines in regions with sparse texture, such as satellite's brackets, some existing line matching methods do not work well due to the incorrect location of line endpoints and line fragments. In this paper, we study how to automatically match low-textured lines. The designed feature only uses their neighborhood appearance and there are no any other prior knowledge or constraints needed. We combine point and line features to propose a novel line matching method. It includes the following three main steps. First, line extraction based on pixel gradient is adopted and we design a mergence strategy to ensure continuity. Then, line-point invariant and center-symmetric local binary pattern descriptor are combined together to represent lines. Last, two corresponding criterions are designed to measure the similarities between each pair images. Extensive experiments on real and synthetic images show that our proposed method exceeds the reference methods in performance under scale, illumination, and dynamic cases.

中文翻译：

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系留空间机器人近距离导航中低纹理区域的线条提取与匹配

在处理具有稀疏纹理的区域中的线条时，例如卫星的括号，由于线条端点和线条片段的位置不正确，一些现有的线条匹配方法效果不佳。在本文中，我们研究如何自动匹配低纹理线。设计的特征仅使用它们的邻域外观，不需要任何其他先验知识或约束。我们结合点和线特征提出了一种新颖的线匹配方法。它包括以下三个主要步骤。首先，采用基于像素梯度的线提取，并设计了合并策略以确保连续性。然后，线点不变和中心对称的局部二进制模式描述符组合在一起来表示线。最后的，设计了两个相应的标准来衡量每对图像之间的相似性。对真实和合成图像的大量实验表明，我们提出的方法在尺度、光照和动态情况下的性能超过了参考方法。