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Feature Extraction from Whole-Sky Ground-Based Images for Cloud-Type Recognition

Several features that can be extracted from digital images of the sky and that can be useful for cloud-type classification of such images are presented. Some features are statistical measurements of image texture, some are based on the Fourier transform of the image and, finally, others are computed from the image where cloudy pixels are distinguished from clear-sky pixels. The use of the most suitable features in an automatic classification algorithm is also shown and discussed. Both the features and the classifier are developed over images taken by two different camera devices, namely, a total sky imager (TSI) and a whole sky imager (WSC), which are placed in two different areas of the world (Toowoomba, Australia; and Girona, Spain, respectively). The performance of the classifier is assessed by comparing its image classification with an a priori classification carried out by visual inspection of more than 200 images from each camera. The index of agreement is 76% when five different sky conditions are considered: clear, low cumuliform clouds, stratiform clouds (overcast), cirriform clouds, and mottled clouds (altocumulus, cirrocumulus). Discussion on the future directions of this research is also presented, regarding both the use of other features and the use of other classification techniques

漏 Journal of Atmospheric and Oceanic Technology, 2008, vol. 25, p. 3-14

American Meteorological Society

Author: Calb贸 Angrill, Josep
Sabburg, Jeff
Date: 2008
Abstract: Several features that can be extracted from digital images of the sky and that can be useful for cloud-type classification of such images are presented. Some features are statistical measurements of image texture, some are based on the Fourier transform of the image and, finally, others are computed from the image where cloudy pixels are distinguished from clear-sky pixels. The use of the most suitable features in an automatic classification algorithm is also shown and discussed. Both the features and the classifier are developed over images taken by two different camera devices, namely, a total sky imager (TSI) and a whole sky imager (WSC), which are placed in two different areas of the world (Toowoomba, Australia; and Girona, Spain, respectively). The performance of the classifier is assessed by comparing its image classification with an a priori classification carried out by visual inspection of more than 200 images from each camera. The index of agreement is 76% when five different sky conditions are considered: clear, low cumuliform clouds, stratiform clouds (overcast), cirriform clouds, and mottled clouds (altocumulus, cirrocumulus). Discussion on the future directions of this research is also presented, regarding both the use of other features and the use of other classification techniques
Format: application/pdf
ISSN: 0739-0572 (versi贸 paper)
1520-0426 (versi贸 electr貌nica)
Document access: http://hdl.handle.net/10256/8462
Language: eng
Publisher: American Meteorological Society
Collection: Reproducci贸 digital del document publicat a: http://dx.doi.org/10.1175/2007JTECHA959.1
Articles publicats (D-F)
Is part of: 漏 Journal of Atmospheric and Oceanic Technology, 2008, vol. 25, p. 3-14
Rights: Tots els drets reservats
Subject: Meteorologia
Meteorology
Title: Feature Extraction from Whole-Sky Ground-Based Images for Cloud-Type Recognition
Type: info:eu-repo/semantics/article
Repository: DUGiDocs

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