Road extraction from high-resolution remote sensing images based on the combination of K-means and SVM

Yanmei Wang; Wei Jiang; Pengfei Feng

doi:10.1117/12.2671264

16 March 2023 Road extraction from high-resolution remote sensing images based on the combination of K-means and SVM

Yanmei Wang, Wei Jiang, Pengfei Feng

Proceedings Volume 12593, Second Guangdong-Hong Kong-Macao Greater Bay Area Artificial Intelligence and Big Data Forum (AIBDF 2022); 125931K (2023) https://doi.org/10.1117/12.2671264
Event: 2nd Guangdong-Hong Kong-Macao Greater Bay Area Artificial Intelligence and Big Data Forum (AIBDF 2022), 2022, Guangzhou, China

Abstract

Extracting road information from high-resolution remote sensing images is an important way to obtain basic data of geographic information. In this paper, firstly, the shortcomings of K-means and SVM are analyzed, and then the road information is extracted by the algorithm combining K-means and SVM. The experimental results show that the combined algorithm has higher accuracy and lower missing error than the single algorithm. The experimental results can provide some technical support for future road information extraction.

Citation Download Citation

Yanmei Wang, Wei Jiang, and Pengfei Feng "Road extraction from high-resolution remote sensing images based on the combination of K-means and SVM", Proc. SPIE 12593, Second Guangdong-Hong Kong-Macao Greater Bay Area Artificial Intelligence and Big Data Forum (AIBDF 2022), 125931K (16 March 2023); https://doi.org/10.1117/12.2671264

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