Remote sensing image building detection method based on Mask R-CNN

Abstract Quickly and conveniently identifying buildings in disaster areas plays an important role assessment. To achieve the technical requirements of flood relief projects, this paper proposes a building extraction method for use with remote sensing images that combines traditional digital image processing methods convolution neural networks. First, threshold segmentation is used to select construct training dataset. Then, variety preprocessing are enhance selected Finally, improved Mask R-CNN algorithm detect images. Experiments show compared algorithm, proposed improves detection accuracy reduces computational time.