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Remote Sens. 2017, 9(1), 40; doi:10.3390/rs9010040

AssesSeg—A Command Line Tool to Quantify Image Segmentation Quality: A Test Carried Out in Southern Spain from Satellite Imagery

1
DICATECh, Politecnico di Bari, Via Orabona 4, Bari 70125, Italy
2
Escuela Superior de Ingeniería de la Universidad de Almeria (UAL), Almeria, Ctra. Sacramento, s/n, La Cañada de San Urbano Almería 04120, Spain
*
Author to whom correspondence should be addressed.
Academic Editors: Guoqing Zhou and Prasad S. Thenkabail
Received: 4 November 2016 / Revised: 9 December 2016 / Accepted: 28 December 2016 / Published: 5 January 2017
View Full-Text   |   Download PDF [3432 KB, uploaded 5 January 2017]   |  

Abstract

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 (Almería). 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. View Full-Text
Keywords: AssesSeg; segmentation quality; greenhouses; Sentinel-2 Multi Spectral Instrument (MSI); Landsat 8 Operational Land Imager (OLI); WorldView-2 (WV2) AssesSeg; segmentation quality; greenhouses; Sentinel-2 Multi Spectral Instrument (MSI); Landsat 8 Operational Land Imager (OLI); WorldView-2 (WV2)
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Novelli, A.; Aguilar, M.A.; Aguilar, F.J.; Nemmaoui, A.; Tarantino, E. AssesSeg—A Command Line Tool to Quantify Image Segmentation Quality: A Test Carried Out in Southern Spain from Satellite Imagery. Remote Sens. 2017, 9, 40.

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