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Directional Enlacement Histograms for the Description of Complex Spatial Configurations between Objects

机译:用于描述对象之间复杂空间配置的方向包络直方图

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摘要

The analysis of spatial relations between objects in digital images plays a crucial role in various application domains related to pattern recognition and computer vision. Classical models for the evaluation of such relations are usually sufficient for the handling of simple objects, but can lead to ambiguous results in more complex situations. In this article, we investigate the modeling of spatial configurations where the objects can be imbricated in each other. We formalize this notion with the term enlacement, from which we also derive the term interlacement, denoting a mutual enlacement of two objects. Our main contribution is the proposition of new relative position descriptors designed to capture the enlacement and interlacement between two-dimensional objects. These descriptors take the form of circular histograms allowing to characterize spatial configurations with directional granularity, and they highlight useful invariance properties for typical image understanding applications. We also show how these descriptors can be used to evaluate different complex spatial relations, such as the surrounding of objects. Experimental results obtained in the different application domains of medical imaging, document image analysis and remote sensing, confirm the genericity of this approach.
机译:在数字图像中对象之间的空间关系分析在与模式识别和计算机视觉有关的各种应用领域中起着至关重要的作用。评估这种关系的经典模型通常足以处理简单的对象,但是在更复杂的情况下可能导致模棱两可的结果。在本文中,我们研究了空间构型的建模,对象之间可以相互缠绕。我们用术语“包含”来正式化这个概念,从中我们也衍生出术语“隔行”,表示两个对象的相互包含。我们的主要贡献是提出了新的相对位置描述符的命题,该描述符旨在捕获二维对象之间的交错和交错。这些描述符采用圆形直方图的形式,允许使用方向粒度来表征空间配置,并且突出显示了典型图像理解应用程序有用的不变性。我们还将展示如何使用这些描述符来评估不同的复杂空间关系,例如对象的周围环境。在医学成像,文档图像分析和遥感的不同应用领域中获得的实验结果证实了这种方法的通用性。

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