Shape Matching Using Point Context and Contour Segments
Shape Matching Using Point Context and Contour Segments
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DOI：
10.1007/978-3-319-16817-3_7
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发表时间：
2014-11
期刊：
影响因子：
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通讯作者：
Christian Feinen;Cong Yang;O. Tiebe;M. Grzegorzek
中科院分区：
文献类型：
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作者：
Christian Feinen;Cong Yang;O. Tiebe;M. Grzegorzek
本文提出了一种新的方法来产生强大的轮廓划分点，并将其应用于产生点上下文和轮廓段特征的形状匹配。其主要思想是通过匹配轮廓分割点和轮廓段来匹配目标形状。与典型的形状上下文方法相比，我们不考虑拓扑图结构，因为我们的方法只考虑少量的分区点，而不是完整的轮廓点。实验结果表明，我们的方法是能够产生正确的结果，在存在的关节，拉伸和轮廓变形。本文最重要的科学贡献包括：（i）引入了一种新的分割点提取技术，用于点上下文和轮廓段，以及（ii）一种新的融合相似性度量，用于对象匹配和识别，以及（iii）该方法在对象检索场景中以及在环境微生物识别的真实的应用中具有令人印象深刻的鲁棒性。
This paper proposes a novel method to generate robust contour partition points and applies them to produce point context and contour segment features for shape matching. The main idea is to match object shapes by matching contour partition points and contour segments. In contrast to typical shape context method, we do not consider the topological graph structure since our approach is only considering a small number of partition points rather than full contour points. The experimental results demonstrate that our method is able to produce correct results in the presence of articulations, stretching, and contour deformations. The most significant scientific contributions of this paper include (i) the introduction of a novel partition point extraction technique for point context and contour segments as well as (ii) a new fused similarity measure for object matching and recognition, and (iii) the impressive robustness of the method in an object retrieval scenario as well as in a real application for environmental microorganism recognition.