首页> 外文会议>第21届国际摄影测量与遥感大会(ISPRS 2008)论文集 >AUTOMATIC BUILDING EXTRACTION FROM HIGH RESOLUTION AERIAL IMAGES USING ACTIVE CONTOUR MODEL
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AUTOMATIC BUILDING EXTRACTION FROM HIGH RESOLUTION AERIAL IMAGES USING ACTIVE CONTOUR MODEL

机译:使用主动轮廓模型从高分辨率航空图像中自动提取建筑物

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Various governmental organizations need accurate, correct and up to date information for optimization of resource and service management. In this issue, geospatial information is very important. Geospatial information as essential part of Geospatial Information System (GIS) has important role in performance of civil projects, urban service management. Using conventional surveying methods for producing geospatial data require a lot of cost and time. Thus, utilization of modern methods in production and updating of this kind of data is necessary. Photogrammetry and Remote Sensing are methods that produce geospatial data in extensive area with acceptable accuracy. In various countries of the world, many researches have been carried out and many algorithms have been introduced in order to decrease human operation in automatic feature extraction of satellite images. Building is one of the features that take the maximum of time and cost of feature extraction due to its abundance in urban area. As a result, on access to a model or algorithm of automatic or semi-automatic extraction of this feature not only minimizes human role in producing large scale maps but also has a dramatic effect on time and cost of the project. The aim of this paper is automatic extraction of boundary of this feature from high resolution aerial images in a way that its output is a vector map that needs the least editing in GIS. the main goal of this research is to introduce a method based on active contour model that the initialization stage of algorithm can be carried out automatically and active contour be ultimately optimized in building extraction. A new model is also suggested for automatic detection and extraction of boundary of buildings. New model of active contour can detect and extract boundary of building very accurately compared to classical model of active contour model and avoid detection of the boundary of features that are in neighbor of buildings such as streets and trees. The result of applying this model shows that the active contour model works better than other models of detection and extraction of building boundaries in urban area.
机译:各种政府组织需要准确,正确和最新的信息来优化资源和服务管理。在此问题中,地理空间信息非常重要。地理空间信息作为地理空间信息系统(GIS)的重要组成部分,在土建项目,城市服务管理中起着重要作用。使用常规的测量方法来产生地理空间数据需要大量的成本和时间。因此,有必要在生产和更新此类数据中使用现代方法。摄影测量和遥感是可以在可接受的精度范围内产生大范围地理空间数据的方法。在世界各个国家,为了减少卫星图像自动特征提取中的人为操作,已经进行了许多研究并且引入了许多算法。由于建筑物数量众多,建筑物是需要花费大量时间和成本来提取特征的建筑物之一。结果,在访问自动或半自动提取的模型或算法时,不仅可以最大程度地减少人在制作大规模地图中的作用,而且还对项目的时间和成本产生了巨大影响。本文的目的是从高分辨率的航拍图像中自动提取该特征的边界,其方式是其输出是在GIS中需要最少编辑的矢量图。本研究的主要目的是介绍一种基于主动轮廓模型的方法,该算法可以自动执行算法的初始化阶段,并在建筑物提取中最终优化主动轮廓。还提出了一种用于自动检测和提取建筑物边界的新模型。与活动轮廓模型的经典模型相比,新的活动轮廓模型可以非常准确地检测和提取建筑物的边界,并且避免检测建筑物附近的要素(例如街道和树木)的边界。应用该模型的结果表明,主动轮廓模型比其他检测和提取市区建筑物边界的模型效果更好。

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