Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.14279/1768
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Eichmann, George | - |
dc.contributor.author | Kasparis, Takis | - |
dc.contributor.other | Κασπαρής, Τάκης | - |
dc.date.accessioned | 2013-02-19T15:46:40Z | en |
dc.date.accessioned | 2013-05-17T05:22:05Z | - |
dc.date.accessioned | 2015-12-02T09:55:08Z | - |
dc.date.available | 2013-02-19T15:46:40Z | en |
dc.date.available | 2013-05-17T05:22:05Z | - |
dc.date.available | 2015-12-02T09:55:08Z | - |
dc.date.issued | 1988-03 | - |
dc.identifier.citation | Computer Vision, Graphics and Image Processing, 1988, Volume 41, Issue 3, Pages 267-281 | en_US |
dc.identifier.issn | 0734189X | - |
dc.identifier.uri | https://hdl.handle.net/20.500.14279/1768 | - |
dc.description.abstract | Texture is one of the important image characteristics and is used to identify objects or regions of interest. The problem of texture classification has been widely studied. Texture classification techniques are either statistical or structural. Some statistical texture classification approaches use Fourier power-spectrum features, while others are based on first- and second-order statistics of gray level differences. Periodic textures that consist of mostly straight lines are of particular interest. In this paper, a new structural approach based on the Hough method of line detection is introduced. This classification is based on the relative orientation and location of the lines within the texture. With proper normalization, the classification is independent of geometrical transformations such as rotation, translation, and/or scaling. Experimental results will also be presented. | en_US |
dc.format | en_US | |
dc.language.iso | en | en_US |
dc.relation.ispartof | Computer Vision, Graphics and Image Processing | en_US |
dc.rights | © 1988 by Academic Press | en_US |
dc.subject | Image processing | en_US |
dc.subject | Image analysis | en_US |
dc.subject | Algorithms | en_US |
dc.subject | Topology | en_US |
dc.title | Topologically invariant texture descriptors | en_US |
dc.type | Article | en_US |
dc.collaboration | City University of New York | en_US |
dc.subject.category | Electrical Engineering - Electronic Engineering - Information Engineering | en_US |
dc.journals | Subscription Journal | en_US |
dc.country | United States | en_US |
dc.subject.field | Engineering and Technology | en_US |
dc.publication | Peer Reviewed | en_US |
dc.identifier.doi | 10.1016/0734-189X(88)90102-8 | en_US |
dc.dept.handle | 123456789/54 | en |
cut.common.academicyear | 2019-2020 | en_US |
item.grantfulltext | none | - |
item.openairecristype | http://purl.org/coar/resource_type/c_6501 | - |
item.fulltext | No Fulltext | - |
item.languageiso639-1 | en | - |
item.cerifentitytype | Publications | - |
item.openairetype | article | - |
crisitem.journal.journalissn | 0734-189X | - |
crisitem.journal.publisher | Elsevier | - |
crisitem.author.dept | Department of Electrical Engineering, Computer Engineering and Informatics | - |
crisitem.author.faculty | Faculty of Engineering and Technology | - |
crisitem.author.orcid | 0000-0003-3486-538x | - |
crisitem.author.parentorg | Faculty of Engineering and Technology | - |
Appears in Collections: | Άρθρα/Articles |
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