A technique for optimal selection of segmentation scale parameters for object-oriented classification of urban scenes

dc.contributor.authorIkokou, Guy Blanchard
dc.contributor.authorSmit, Julian
dc.date.accessioned2017-10-31T08:47:33Z
dc.date.available2017-10-31T08:47:33Z
dc.date.issued2013
dc.date.updated2017-10-31T06:55:56Z
dc.description.abstractMulti-scale image segmentation produces high level object features at more than one level, compared to single scale segmentation. Objects generated from this type of segmentation hold additional attributes such as mean values per spectral band, distances to neighbouring objects, size, and texture, as well as shape characteristics. However, the accuracy of these high level features depends on the choice of segmentation scale parameters. Several studies have investigated techniques for scale parameter selection. These proposed approaches do not consider the different objects’ size variability found in complex scenes such as urban scene as they rely upon arbitrary object size measures, introducing instability errors when computing image variances. A technique to select optimal segmentation scale parameters based on image variance and spatial autocorrelation is presented in this paper. Optimal scales satisfy simultaneously the conditions of low object internal variance and high inter-segments spatial autocorrelation. Applied on three Cape Town urban scenes, the technique produced visually promising results that would improve object extraction over urban areas.
dc.identifier.apacitationIkokou, G. B., & Smit, J. (2013). A technique for optimal selection of segmentation scale parameters for object-oriented classification of urban scenes. <i>South African Journal of Geomatics</i>, http://hdl.handle.net/11427/25936en_ZA
dc.identifier.chicagocitationIkokou, Guy Blanchard, and Julian Smit "A technique for optimal selection of segmentation scale parameters for object-oriented classification of urban scenes." <i>South African Journal of Geomatics</i> (2013) http://hdl.handle.net/11427/25936en_ZA
dc.identifier.citationIkokou, Guy Blanchard, and Julian Smit. "A technique for optimal selection of segmentation scale parameters for object-oriented classification of urban scenes." South African Journal of Geomatics 2, no. 4 (2013): 358-369.
dc.identifier.ris TY - Journal Article AU - Ikokou, Guy Blanchard AU - Smit, Julian AB - Multi-scale image segmentation produces high level object features at more than one level, compared to single scale segmentation. Objects generated from this type of segmentation hold additional attributes such as mean values per spectral band, distances to neighbouring objects, size, and texture, as well as shape characteristics. However, the accuracy of these high level features depends on the choice of segmentation scale parameters. Several studies have investigated techniques for scale parameter selection. These proposed approaches do not consider the different objects’ size variability found in complex scenes such as urban scene as they rely upon arbitrary object size measures, introducing instability errors when computing image variances. A technique to select optimal segmentation scale parameters based on image variance and spatial autocorrelation is presented in this paper. Optimal scales satisfy simultaneously the conditions of low object internal variance and high inter-segments spatial autocorrelation. Applied on three Cape Town urban scenes, the technique produced visually promising results that would improve object extraction over urban areas. DA - 2013 DB - OpenUCT DP - University of Cape Town J1 - South African Journal of Geomatics LK - https://open.uct.ac.za PB - University of Cape Town PY - 2013 T1 - A technique for optimal selection of segmentation scale parameters for object-oriented classification of urban scenes TI - A technique for optimal selection of segmentation scale parameters for object-oriented classification of urban scenes UR - http://hdl.handle.net/11427/25936 ER - en_ZA
dc.identifier.urihttp://hdl.handle.net/11427/25936
dc.identifier.vancouvercitationIkokou GB, Smit J. A technique for optimal selection of segmentation scale parameters for object-oriented classification of urban scenes. South African Journal of Geomatics. 2013; http://hdl.handle.net/11427/25936.en_ZA
dc.language.isoeng
dc.publisher.departmentSchool of Architecture, Planning and Geomatics
dc.publisher.facultyFaculty of Engineering and the Built Environment
dc.publisher.institutionUniversity of Cape Town
dc.sourceSouth African Journal of Geomatics
dc.source.urihttp://www.sajg.org.za/index.php/sajg/index
dc.subject.othersegmentation
dc.subject.otherobject oriented classification
dc.subject.otherobject’s variance
dc.subject.otherspatial autocorrelation
dc.subject.otherobjective function
dc.subject.otherMoran’s index
dc.titleA technique for optimal selection of segmentation scale parameters for object-oriented classification of urban scenes
dc.typeJournal Article
uct.type.filetypeText
uct.type.filetypeImage
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