Automatic Coastline Detection Using Image Enhancement and Segmentation Algorithms
| Autor: | Erdem Emin Maraş, Hadi Hakan Maras, Mustafa Caniberk |
|---|---|
| Přispěvatelé: | OMÜ |
| Jazyk: | angličtina |
| Rok vydání: | 2016 |
| Předmět: |
edge detection
0209 industrial biotechnology Segmentation-based object categorization Computer science business.industry segmentation 0211 other engineering and technologies Scale-space segmentation 02 engineering and technology Image segmentation integrated coastal zone management (ICZM) Edge detection coastlines 020901 industrial engineering & automation Environmental Chemistry Segmentation Computer vision Artificial intelligence business 021101 geological & geomatics engineering General Environmental Science |
| Popis: | Maras, Hakan/0000-0001-5117-3938 WOS: 000388734500028 Coastlines have hosted numerous civilizations since the earliest times of mankind due to the advantages they offer such as natural resources, transportation, arable areas, seafood, trade, and biodiversity. Coastal regions should be monitored vigilantly by planners and control mechanisms, and any changes in these regions should be detected with its human or natural origin, and future plans and possible interventions should be formed in these aspects to maintain ecological balance, sustainable development, and planned urbanization. Integrated coastal zone management (ICZM) provides an important tool to reach that goal. One of the important elements of ICZM is the detection of coastlines. While there are several methods to detect coastlines, remote sensing methods provide the fastest and the most efficient solutions. In this study, color infrared, grayscale, RGB, and fake infrared images were processed with the median filtering and segmentation software developed within the study, and coastal lines were detected by the edge detection method. The results show that segmentation with fake infrared images derived from RGB images give the best results. |
| Databáze: | OpenAIRE |
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