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oai:www.ideals.illinois.edu:2142/80974 2023-07-11 col_2142_5131 col_2142_8888 com_2142_5130 com_2142_8887 com_2142_234

Ma, Yi Hong, Wei 2015-09-25T20:09:03Z 2015-09-25T20:09:03Z 10000-01-01 2006 2006 In this dissertation, we also address multimodal structures in textures by proposing a directional hybrid linear model, which combines linear hybrid models with directional filters and provides a deterministic representation of textures. Such a hybrid linear representation allows us to naturally deal with multiple textures that may appear in a single image, thus greatly facilitating texture segmentation and recognition. We discuss how this simple yet powerful representation is related to and in fact encompasses previous models in the literature, and demonstrate its applications in texture segmentation and texture recognition. Made available in DSpace on 2015-09-25T20:09:03Z (GMT). No. of bitstreams: 2 license.txt: 4848 bytes, checksum: 96035ab3f5e1c23cc7138a224ce498bd (MD5) 3242873.pdf: 3510298 bytes, checksum: f60f5ce175c73f061f445368bb5c05b3 (MD5) Previous issue date: 2006 Embargo set by: Seth Robbins for item 82256 Lift date: Forever Reason: Restricted to the U of I community idenfinitely during batch ingest of legacy ETDs Restricted to the U of I community idenfinitely during batch ingest of legacy ETDs U of I Only 98 p. Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2006. http://hdl.handle.net/2142/80974 (MiAaPQ)AAI3242873 eng Engineering, Electronics and Electrical Hybrid Models for Representation of Imagery Data text Electrical and Computer Engineering Electrical and Computer Engineering University of Illinois at Urbana-Champaign Dissertation Ph.D.