Paper
14 November 2023 Research and application of water shoreline extraction technology
Zhanzhao Zhong, Liling Zhou, Ying Zhang
Author Affiliations +
Proceedings Volume 12934, Third International Conference on Computer Graphics, Image, and Virtualization (ICCGIV 2023); 129341T (2023) https://doi.org/10.1117/12.3008014
Event: 2023 3rd International Conference on Computer Graphics, Image and Virtualization (ICCGIV 2023), 2023, Nanjing, China
Abstract
This topic is mainly aimed at the limitations of traditional water coastline segmentation and extraction technology. Through the comparison and analysis of different neural network algorithms, a water coastline recognition and extraction method based on VGG16-U-Net network is proposed to improve the quality of the water coastline. Recognition ability and accuracy of high-resolution images. This study uses the UAV aerial photography data set,uses the pre-training model and the improved VGG+Unet-based enhanced feature extraction network structure for training, and finally marks the water coastline on the original image and generates corresponding picture. This paper first introduces the research background and related technologies, then analyzes the structure and principle of the algorithm model used, and elaborates the specific implementation process and modification testing process. The innovation of this paper is based on the symmetrical structure of the U-Net network, combined with the VGG16 model to replace the original Unet’s backbone feature extraction network, double upsampling in the upsampling, and finally feature fusion, the obtained feature layer and the height and width of the original image are the same, which improves the accuracy of image recognition.
(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Zhanzhao Zhong, Liling Zhou, and Ying Zhang "Research and application of water shoreline extraction technology", Proc. SPIE 12934, Third International Conference on Computer Graphics, Image, and Virtualization (ICCGIV 2023), 129341T (14 November 2023); https://doi.org/10.1117/12.3008014
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KEYWORDS
Image segmentation

Education and training

Data modeling

Image processing

Coastal modeling

Mathematical optimization

Feature extraction

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