Building extraction method based on prior shape level set segmentation

Abstract

The invention provides a building extraction method based on prior shape level set segmentation in order to overcome the shortcomings that the conventional building extraction technology is sensitive to noise and low in extraction precision, and depends on a segmentation result. According to the basic idea of the building extraction method based on the prior shape level set segmentation, urban building extraction is carried out in two steps, wherein in the first step, a rough outline of a building in altitude data is extracted, and morphological filtering and small-region removal are performed on the altitude data to obtain a final building distribution binary graph, and in the second step, outline information of the building is extracted in an optical image of an unmanned aerial vehicle, the building distribution binary graph serving as prior information is introduced into a level set segmentation model, and an evolution initial position and a prior outline are supplied to the model, so that the segmentation result is a building outline information extraction result. The building extraction method has the advantages of high pertinence and high precision.

Description

technical field [0001] The invention belongs to the technical field of computer digital image processing and pattern recognition, and mainly relates to a method for identifying urban buildings, in particular to a method for extracting buildings based on remote sensing images of drones. Background technique [0002] The extraction of urban building outline information is not yet a good algorithm with a wide range of applications. Traditional engineering uses manual interpretation and manual sketching, which is low in efficiency and labor-intensive. Therefore, the automatic extraction technology of building outline information has become an important research topic in the field of target recognition. At present, the main methods for automatic extraction of building outline information are: [0003] 1. Building extraction technology based on geometric features [0004] The common ground based on geometric features is to use low-level visual technology to extract geometric ele...

AI Technical Summary

Problems solved by technology

[0005] This type of method currently achieves good results in detecting regular houses and rural images with low house density and simple structure, but for general images, there are still many problems: (1) Due to the influence of factors such as noise, shadows and occlusions, It is often impossible to obtain continuous edges or line segments; (2) A large number of noisy edges will increase the calculation amount of target detection sharply, and even lead to wrong detection results

Its disadvantage is that the accuracy of building extraction is extremely dependent on the accuracy of image segmentation

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