Automatic contour segmentation for object analysis

D. Hung, I. Chen
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Abstract

The problem of distinguishing shapes from a compound contour, which is formed by overlapping more than one distinct object, is considered. The algorithm exploits the fact that planar shapes can be completely described by contour segments, and that they can be decomposed at their maximum concavity into simpler objects. To reduce spurious decomposition, the decomposed segments are merged hypotheses. The algorithm calculates the linking possibility by weighting the angular differentiation which measures against k-curvature consistency. The techniques were implemented and applied to other partial shape matching problems for clustering purposes.<>
用于对象分析的自动轮廓分割
考虑了由多个不同物体重叠而成的复合轮廓的形状识别问题。该算法利用了平面形状可以完全由轮廓段描述的事实,并且可以在其最大凹度处将其分解为更简单的对象。为了减少虚假分解,将分解的片段合并为假设。该算法通过加权衡量k曲率一致性的角微分来计算连接可能性。这些技术被实现并应用于其他以聚类为目的的部分形状匹配问题。
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