Automated Coastline Extraction Using Edge Detection Algorithms

Fuente: arXiv
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Main Authors: O'Sullivan, Conor, Coveney, Seamus, Monteys, Xavier, Dev, Soumyabrata
Format: Preprint
Published: 2024
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author O'Sullivan, Conor
Coveney, Seamus
Monteys, Xavier
Dev, Soumyabrata
author_facet O'Sullivan, Conor
Coveney, Seamus
Monteys, Xavier
Dev, Soumyabrata
contents We analyse the effectiveness of edge detection algorithms for the purpose of automatically extracting coastlines from satellite images. Four algorithms - Canny, Sobel, Scharr and Prewitt are compared visually and using metrics. With an average SSIM of 0.8, Canny detected edges that were closest to the reference edges. However, the algorithm had difficulty distinguishing noisy edges, e.g. due to development, from coastline edges. In addition, histogram equalization and Gaussian blur were shown to improve the effectiveness of the edge detection algorithms by up to 1.5 and 1.6 times respectively.
format Preprint
id arxiv_https___arxiv_org_abs_2405_11494
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Automated Coastline Extraction Using Edge Detection Algorithms
O'Sullivan, Conor
Coveney, Seamus
Monteys, Xavier
Dev, Soumyabrata
Computer Vision and Pattern Recognition
Machine Learning
Image and Video Processing
We analyse the effectiveness of edge detection algorithms for the purpose of automatically extracting coastlines from satellite images. Four algorithms - Canny, Sobel, Scharr and Prewitt are compared visually and using metrics. With an average SSIM of 0.8, Canny detected edges that were closest to the reference edges. However, the algorithm had difficulty distinguishing noisy edges, e.g. due to development, from coastline edges. In addition, histogram equalization and Gaussian blur were shown to improve the effectiveness of the edge detection algorithms by up to 1.5 and 1.6 times respectively.
title Automated Coastline Extraction Using Edge Detection Algorithms
topic Computer Vision and Pattern Recognition
Machine Learning
Image and Video Processing
url https://arxiv.org/abs/2405.11494