Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/82916
Title: Categorization of cloud image patches using an improved texton-based approach
Authors: Dev, Soumyabrata
Lee, Yee Hui
Winkler, Stefan
Keywords: Cloud texture
Classification
Groundbased sky imaging
Issue Date: 2015
Source: Dev, S., Lee, Y. H., & Winkler, S. (2015). Categorization of cloud image patches using an improved texton-based approach. 2015 IEEE International Conference on Image Processing (ICIP), 422-426.
Conference: 2015 IEEE International Conference on Image Processing (ICIP)
Abstract: We propose a modified texton-based classification approach that integrates both color and texture information for improved classification results. We test our proposed method for the task of cloud classification on SWIMCAT, a large new database of cloud images taken with a ground-based sky imager, with very good results. We perform an extensive evaluation, comparing different color components, filter banks, and other parameters to understand their effect on classification accuracy. Finally, we release the SWIMCAT dataset that was created for the task of cloud categorization.
URI: https://hdl.handle.net/10356/82916
http://hdl.handle.net/10220/40358
DOI: 10.1109/ICIP.2015.7350833
Schools: School of Electrical and Electronic Engineering 
Rights: © 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The published version is available at: [http://dx.doi.org/10.1109/ICIP.2015.7350833].
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:EEE Conference Papers

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