Coastline Detection from Remote Sensing Image Based on K-Mean Cluster and Distance Transform Algorithm

Ying Liu

doi:10.4028/www.scientific.net/AMR.760-762.1567

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 760-762Coastline Detection from Remote Sensing Image...

Coastline Detection from Remote Sensing Image Based on K-Mean Cluster and Distance Transform Algorithm

Abstract:

Using remote sensing technique to determine coastline's position has been received vital attention. This paper presents a novel approach for detecting coastline of remote sensing image based on K-Means cluster and Distance Transform algorithm. K-Means cluster algorithm divides the image into two regions-water and land area. Then to extract the sea area by distance transfoming. Finally, the coastline will be detected by edge traking. Results showed that the method proposed in this paper have good performance in accuracy and completeness.

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Periodical:

Advanced Materials Research (Volumes 760-762)

Pages:

1567-1571

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.760-762.1567

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Online since:

September 2013

Authors:

Ying Liu

Keywords:

Coastline Detection, Distance Transform, K-Mean

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References

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