Building recognition method based on multi-feature fusion

Abstract

The invention provides a building identification method based on multi-feature fusion, which comprises the following steps: extracting Gabor-HOG feature from an input multi-spectral image; fusing theextracted Gabor-HOG feature and RGB color feature to form low-level feature vector. The low-level eigenvectors are inputted into the trained deep confidence network model to extract the high-level eigenvectors and generate the posterior probability of each pixel. The posterior probability of each pixel is inputted into the trained conditional random field model, and the contextual feature of the neighborhood information of each pixel is extracted, and the building target is identified according to the maximum posterior probability. As the low-level visual characteristic are designed, by usingdeep confidence network to extract high-rise building features and conditional random field to extract building context features, the problems of low building recognition rate caused by simplificationof building feature extraction and low building recognition rate caused by traditional methods are solved, and the precision and recall rate of building recognition can be improved.

Description

technical field [0001] The invention belongs to the technical field of image recognition, and in particular relates to a building recognition method based on multi-feature fusion. Background technique [0002] With the continuous development of aerospace technology, more and more remote sensing data are obtained, how to make full use of remote sensing data is particularly important. Buildings are an important class of ground objects. How to accurately identify them has become a research hotspot in the fields of image processing, pattern recognition, and artificial intelligence. [0003] At present, for multispectral images obtained by different aircraft, there are many algorithms and improved algorithms to identify buildings in the images. However, due to the different channels of image acquisition, it is often necessary to extract different features when identifying buildings in different images, and find the best feature extraction method for this type of image through ex...

AI Technical Summary

Problems solved by technology

In order to solve the problem of low building recognition rate caused by the simplification of building feature extraction and traditional methods only extracting low-level features, improve the precision and recall rate of building recognition

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