C_AssesSeg Concurrent Computing Version of AssesSeg: A Benchmark Between the New and Previous Version
| Autor: | Fernando J. Aguilar, Abderrahim Nemmaoui, Antonio Novelli, Manuel A. Aguilar, Eufemia Tarantino |
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| Rok vydání: | 2017 |
| Předmět: |
Source code
AssesSeg 010504 meteorology & atmospheric sciences Landsat 8 operational land imager (OLI) Computer science media_common.quotation_subject 0211 other engineering and technologies 02 engineering and technology 01 natural sciences Theoretical Computer Science Digital image Segmentation quality Sentinel-2 multi spectral instrument (MSI) WorldView-2 (WV2) WorldView-3 (WV3) Computer Science (all) Computer graphics (images) Concurrent computing Segmentation 021101 geological & geomatics engineering 0105 earth and related environmental sciences media_common computer.programming_language computer.file_format Python (programming language) Euclidean distance Executable computer |
| Zdroj: | Computational Science and Its Applications – ICCSA 2017 ISBN: 9783319624006 ICCSA (4) |
| DOI: | 10.1007/978-3-319-62401-3_4 |
| Popis: | This paper presents the capabilities of a command line tool (.exe) created to assess the quality of segmented digital images. The executable source code, called AssesSeg (Assess Segmentation), was written in Python 2.7 using only open source libraries. AssesSeg 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, WorldView-2 and WorldView-3). The segmentation was applied to plastic covered greenhouse detection in the south of Spain (Almeria). AssesSeg 2.0 was compared with the previous version computing time. The comparisons showed how the new version can benefit from modern multi-core CPU. |
| Databáze: | OpenAIRE |
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