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Automated Detection and Classification for Craters Based on Geometric Matching

机译:基于几何匹配的陨石坑自动检测与分类

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Crater detection and classification are critical elements for planetary mission preparations and landing site selection. This paper presents a methodology for the automated detection and matching of craters on images of planetary surface such as Moon, Mars and asteroids. For craters usually are bowl shaped depression, craters can be figured as circles or circular arc during landing phase. Based on the hypothesis that detected crater edges is related to craters in a template by translation, rotation and scaling, the proposed matching method use circles to fitting craters edge, and align circular arc edges from the image of the target body with circular features contained in a model. The approach includes edge detection, edge grouping, reference point detection and geometric circle model matching. Finally we simulate planetary surface to test the reasonableness and effectiveness of the proposed method.
机译:陨石坑的检测和分类是行星任务准备和着陆点选择的关键要素。本文提出了一种自动检测和匹配月球,火星和小行星等行星表面图像上的陨石坑的方法。对于环形山来说,环形山通常是碗状的凹陷,环形山在着陆阶段可以算作圆形或圆弧形。基于通过平移,旋转和缩放检测到的陨石坑边缘与模板中的陨石坑相关的假设,提出的匹配方法使用圆来拟合陨石坑边缘,并将目标物体图像中的圆弧边缘与包含在其中的圆形特征对齐一个模型。该方法包括边缘检测,边缘分组,参考点检测和几何圆模型匹配。最后,我们通过模拟行星表面来检验所提方法的合理性和有效性。

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