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Automatic urban building boundary extraction from high resolution aerial images using an innovative model of active contours

机译:使用主动轮廓的创新模型从高分辨率航拍图像中自动提取城市建筑边界

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To present a new method for building boundary detection and extraction based on the active contour model, is the main objective of this research. Classical models of this type are associated with several shortcomings; they require extensive initialization, they are sensitive to noise, and adjustment issues often become problematic with complex images. In this research a new model of active contours has been proposed that is optimized for the automatic building extraction. This new active contour model, in comparison to the classical ones, can detect and extract the building boundaries more accurately, and is capable of avoiding detection of the boundaries of features in the neighborhood of buildings such as streets and trees. Finally, the detected building boundaries are generalized to obtain a regular shape for building boundaries. Tests with our proposed model demonstrate excellent accuracy in terms of building boundary extraction. However, due to the radiometric similarity between building roofs and the image background, our system fails to recognize a few buildings.
机译:提出一种基于主动轮廓模型的建筑物边界检测与提取新方法,是本研究的主要目的。这种类型的经典模型存在一些缺点。它们需要大量的初始化,对噪声敏感,并且调整问题对于复杂的图像通常会成为问题。在这项研究中,提出了一种主动轮廓的新模型,该模型针对自动建筑物提取进行了优化。与传统模型相比,这种新的主动轮廓模型可以更准确地检测和提取建筑物边界,并且能够避免检测建筑物附近(如街道和树木)的特征边界。最后,对检测到的建筑物边界进行概括,以获得用于建筑物边界的规则形状。使用我们提出的模型进行的测试证明了建筑物边界提取方面的出色准确性。但是,由于建筑物屋顶和图像背景之间的辐射相似性,我们的系统无法识别一些建筑物。

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