GLCM Texture: A Tutorial v. 3.0 March 2017

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dc.contributor.authorHall-Beyer, Mryka
dc.date.accessioned2017-04-04T17:21:09Z
dc.date.available2017-04-04T17:21:09Z
dc.date.issued2017-03
dc.descriptionOf use generally for students of intermediate or advanced undergraduate remote sensing classes, and graduate classes in remote sensing, landscape ecology, GIS and other fields using rasters as the basis for analysis. Also useful for researchers undertaking the use of texture in classification and other image analysis fields. May be of use for algorithm and app developers serving these communities.en_US
dc.description.abstractThis tutorial describes both the theory and practice of the use of Grey Level Co-occurrence Matrix (GLCM) textures as originally described by Haralick and others in 1973. It leads users through the practical construction and use of a small sample image, with the aim of deep understanding of the purpose, capabilities and limitations of this set of descriptive statistics. Explanations and examples are concentrated on use in a landscape scale and perspective for enhancing classification accuracy, particularly in the cases where spatial arrangement of tonal (spectral) variability provides independent data relevant to the class identification. Background information is provided to answer the questions arising from 15 years of use of the tutorial, and increased practical experience of the author in teaching and research. Some information is provided to make the material accessible to specialists in fields other than remote sensing, for example medical imaging and industrial quality control. However the author is not an expert in these fields and texture's use there is not covered in detail. A basic bibliography is provided for research that has promoted the field of remote sensing GLCM texture; research projects that simply make use of it are not systematically covered.en_US
dc.description.refereedNoen_US
dc.identifier.citationHall-Beyer, M., 2007. GLCM Texture: A Tutorial v. 1.0 through 2.7.en_US
dc.identifier.doihttp://dx.doi.org/10.11575/PRISM/33280
dc.identifier.urihttp://hdl.handle.net/1880/51900
dc.language.isoenen_US
dc.publisherPreviously available at http://www.ucalgary.ca/UofC/nasdev/mhallbey/research.htmen_US
dc.publisher.departmentGeographyen_US
dc.publisher.facultyArtsen_US
dc.publisher.institutionUniversity of Calgaryen_US
dc.publisher.urlhttp://www.ucalgary.ca/UofC/nasdev/mhallbey/research.htmen_US
dc.rightsAttribution Non-Commercial 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/*
dc.subjectremote sensingen_US
dc.subjectspatial descriptorsen_US
dc.subjectspatial statisticsen_US
dc.subjecttextureen_US
dc.subjectGLCMen_US
dc.subjecteducational resourceen_US
dc.titleGLCM Texture: A Tutorial v. 3.0 March 2017en_US
dc.typelearning objecten_US
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Texture tutorial including illustrations, examples and exercises with answers
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