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首页> 外文期刊>Journal of Computers >Line Matching Method Based on Related Points and Geometric Constraints
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Line Matching Method Based on Related Points and Geometric Constraints

机译：基于相关点和几何约束的线匹配方法

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Combining related points and straight lines can increase the feature description ability of lines. However, mismatching problems exist for both points and lines when traditional methods are used. To improve line matching accuracy, this paper proposes a line matching method based on related points and geometric constraints. First, a statistical histogram of matched point pair distance ratios is used to eliminate mismatched SIFT feature points. After line extraction, related points are chosen and used to construct affine invariants describing line features. Lines are subsequently coarsely matched based on affine invariant similarities. Finally, an affine transformation model is calculated and lines are finely matched with line angle and distance constraints. Experimental results demonstrate the method is suitable for images with affine transformation and can obtain more matched line pairs with high accuracy than traditional methods. The proposed method considers both local and global geometric line characteristics and obtains good line matching results for images with complex or simple textures.
机译：结合相关点和直线可以增加线条的特征描述能力。但是，在使用传统方法时，两点和线都存在不匹配的问题。为了提高线路匹配精度，本文提出了一种基于相关点和几何约束的线匹配方法。首先，使用匹配点对距离比的统计直方图来消除不匹配的筛选特征点。在线提取后，选择相关点并用于构建描述线特征的仿射不变。随后基于仿射不变相似性粗略地匹配线。最后，计算仿射变换模型，并用线角和距离约束对线进行细配合。实验结果表明，该方法适用于具有仿射变换的图像，并且可以高于传统方法获得更高的精度的匹配线对。所提出的方法考虑本地和全局几何线特征，并获得具有复杂或简单纹理的图像的良好线路匹配结果。

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