A theoretical and experimental analysis related to the effect of noise in the task of vertex identification in unknown shapes is presented. Shapes are seen as real functions of their closed boundary. An alternative global perspective of curvature is examined providing insight into the process of noise-enabled vertex localization. The analysis reveals that noise facilitates in the localization of certain vertices. The concept of noising is thus considered and a relevant global method for localizing Global Vertices is investigated in relation to local methods under the presence of increasing noise. Theoretical analysis reveals that induced noise can indeed help localizing certain vertices if combined with global descriptors. Experiments with noise and a comparison to localized methods validate the theoretical results.

中文翻译：

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噪声在顶点定位中的有益影响

提出了与噪声在未知形状中的顶点识别任务中的影响相关的理论和实验分析。形状被视为其封闭边界的真实函数。检查曲率的另一种全局视角，提供对启用噪声的顶点定位过程的深入了解。分析表明，噪声有助于某些顶点的定位。因此考虑了噪声的概念，并且在存在增加的噪声的情况下研究了与局部方法相关的用于定位全局顶点的相关全局方法。理论分析表明，如果结合全局描述符，诱导噪声确实可以帮助定位某些顶点。噪声实验和与局部方法的比较验证了理论结果。