Abstract
Although determining the type of building can be useful for 3D reconstruction, image retrieval, and other applications, it is often difficult to do so automatically. A building classification algorithm using a geographic information system (GIS) is proposed in this paper. The typical adjustment of building polygon, local convex-concave simplification of large-area polygon contour, and local exaggeration of competing polygon groups merging in small-area polygon is the main topics of this paper. The preliminary outline area is obtained by analyzing the corner characteristics of two basic types of buildings in urban buildings using a large-scale morphological screen. The classification statistics of all kinds of corners are carried out using the improved Hough transform and the proposed line segment and corner optimization algorithm, and the automatic classification of flat-roofed and nonflat-roofed buildings photographed by digital cameras is realized. The experimental results show that the algorithm simplifies the polygons in a reasonable way while maintaining the block shape. Furthermore, the optimization algorithm proposed in this paper effectively eliminates the influence of false contours, allowing for high-accuracy building type judgment.
Highlights
The fineness and complexity of the building model, as one of the most important components of urban basic geographic information, can have a direct impact on the quality and efficiency of 3D urban model application [1]
Use Deformable Parts Models (DPM) to preprocess the architectural style image data set and use the Secondary classification based on Ensemble Projection (SEP) algorithm to classify the preprocessed images
This paper focuses on building classification algorithms based on geographic information system (GIS), based on extensive research and analysis of building classification algorithms both at home and abroad
Summary
The fineness and complexity of the building model, as one of the most important components of urban basic geographic information, can have a direct impact on the quality and efficiency of 3D urban model application [1]. The general development method of building management software separates the management of graphics and attributes, which makes operation and maintenance more difficult. In the application of GIS system, expressing geographic data in three-dimensional visual form is an important means for spatial information expression, query and analysis [6]. This paper uses GIS to present the overall design of a building classification algorithm and to classify architectural style images. The extraction of building area in the image is helpful to realize the automatic classification of the extracted street view. 3D visualization is mainly realized by Digital Elevation Model (DEM) and other data in the GIS system. Based on the assumption of the world of urban buildings, a new image-based algorithm for automatically determining the flat roof and nonflat roof of buildings is proposed.
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