AssesSeg—A Command Line Tool to Quantify Image Segmentation Quality: A Test Carried Out in Southern Spain from Satellite Imagery
| Autor: | Abderrahim Nemmaoui, Manuel A. Aguilar, Fernando J. Aguilar, Antonio Novelli, Eufemia Tarantino |
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| Jazyk: | angličtina |
| Rok vydání: | 2017 |
| Předmět: |
segmentation quality
010504 meteorology & atmospheric sciences AssesSeg Computer science 0211 other engineering and technologies 02 engineering and technology 01 natural sciences greenhouses Digital image Sentinel-2 Multi Spectral Instrument (MSI) Segmentation Computer vision Satellite imagery lcsh:Science 021101 geological & geomatics engineering 0105 earth and related environmental sciences business.industry Image segmentation Landsat 8 Operational Land Imager (OLI) WorldView-2 (WV2) Euclidean distance General Earth and Planetary Sciences lcsh:Q Artificial intelligence Remote Sensing Agriculture business |
| Zdroj: | riUAL. Repositorio Institucional de la Universidad de Almería Universidad de Almería Remote Sensing, Vol 9, Iss 1, p 40 (2017) |
| Popis: | This letter presents the capabilities of a command line tool created to assess the quality of segmented digital images. The executable source code, called AssesSeg, was written in Python 2.7 using open source libraries. AssesSeg (University of Almeria, Almeria, Spain; Politecnico di Bari, Bari, Italy) implements a modified version of the supervised discrepancy measure named Euclidean Distance 2 (ED2) and was tested on different satellite images (Sentinel-2, Landsat 8, and WorldView-2). The segmentation was applied to plastic covered greenhouse detection in the south of Spain (Almeria). AssesSeg outputs were utilized to find the best band combinations for the performed segmentations of the images and showed a clear positive correlation between segmentation accuracy and the quantity of available reference data. This demonstrates the importance of a high number of reference data in supervised segmentation accuracy assessment problems. |
| Databáze: | OpenAIRE |
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