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一种用于破碎骨骼残骸配对匹配的自动二维成对表单配准方法。

An Automated Two-dimensional Pairwise form Registration Method for Pair-matching of Fragmented Skeletal Remains.

作者信息

Lynch Jeffrey James

机构信息

Defense POW/MIA Accounting Agency, 106 Peacekeeper Drive, Bldg 301, Offutt Air Force Base, Omaha, NE, 68113-4006.

出版信息

J Forensic Sci. 2018 Nov;63(6):1790-1795. doi: 10.1111/1556-4029.13787. Epub 2018 Apr 10.

Abstract

This study introduces an automated pairwise method for osteological pair-matching of fragmented skeletal remains using two-dimensional fragmented outlines extracted from photographs. The form data are used in pairwise iterative closest point registrations with rigid transformations. A modified version of the average Hausdorff distance is calculated to remove any coordinate correspondences with outline fracture margins, which allow the distance analysis of fragmented outlines. A dilation modification to the Hausdorff distance is proposed creating a greater separation between true- and false-pairs. The sample consists of 122 calcanei (61 pairs) from the UI-Stanford collection. Performance statistics are provided for simulated fragmented and complete assemblages. Results indicate up to 98% accuracy for fragmented and complete assemblages. The dilated Hausdorff distance performed similarly across assemblages, but showed a slight decrease in performance for the complete assemblage. This approach provides a useful short listing tool to reduce the number of visual comparisons required in large commingled assemblages.

摘要

本研究介绍了一种自动化的成对匹配方法,用于利用从照片中提取的二维破碎轮廓对碎片化骨骼遗骸进行骨学成对匹配。形状数据用于具有刚性变换的成对迭代最近点配准。计算了平均豪斯多夫距离的修改版本,以去除与轮廓骨折边缘的任何坐标对应关系,从而实现对碎片化轮廓的距离分析。提出了对豪斯多夫距离的膨胀修改,以在真对和假对之间产生更大的分离。样本包括来自UI - 斯坦福收藏的122个跟骨(61对)。提供了模拟碎片化和完整组合的性能统计数据。结果表明,碎片化和完整组合的准确率高达98%。膨胀后的豪斯多夫距离在不同组合中的表现相似,但在完整组合中的性能略有下降。这种方法提供了一个有用的筛选工具,以减少大型混合组合中所需的视觉比较数量。

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