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首页> 外文会议>Pixels, Objects, Intelligence: GEOgraphic Object Based Image Analysis for the 21st Century >OBJECT BASED CLASSIFICATION TECHNIQUES IN URBAN CHANGE PLANNING
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OBJECT BASED CLASSIFICATION TECHNIQUES IN URBAN CHANGE PLANNING

机译：城市变革规划的基于对象的分类技术

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Rapid growing of population, a reliable solution is essential to monitor the changes and make the digital map revised. The need of fast decision making and complete control on problems is one of the biggest disturbances of organizers that necessitate the use of up to date information. Most traditional pixel-based classifications are based on the digital number of each pixel. The high spatial resolution images provide more details such as color, size, shape and texture. So the object-oriented processing become of interest. This paper focuses on an automatic change detection method based on object based classification techniques. The first step of the object-oriented processing is the segmentation. Next the object based classification with use of spectral, textural and structural parameters will be used to classify the imagery. Lastly Some Structural Rules such as the ratio of areas and Homogeneity parameters are used to compare the classification image objects and the old digital map to detect the changes. The proposed methodology was tested on a 1:2000 scale digital map of the city of Qom in Iran by using Quick Bird scenes. The visual investigation and the accuracy assessment of the obtained results demonstrate the high capability of this method.
机译：人口快速增长，可靠的解决方案对于监控变化至关重要，并使数字地图修改。需要快速决策和完全控制问题的需要是组织者最大的干扰之一，以便使用最新信息。大多数传统的基于像素的分类基于每个像素的数字数。高空间分辨率图像提供更多细节，例如颜色，大小，形状和纹理。因此面向对象的处理变得感兴趣。本文侧重于基于对象的分类技术的自动变化检测方法。面向对象处理的第一步是分段。接下来，使用频谱，纹理和结构参数的基于对象的分类将用于对图像进行分类。最后一些结构规则，例如区域和同质性参数的比率用于比较分类图像对象和旧数字地图以检测变化。通过使用快速鸟类场景，在伊朗的1：2000规模的数字地图上测试了拟议的方法。所获得的结果的视觉调查和准确性评估证明了该方法的高能力。

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