Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.14279/2505
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Kasparis, Takis | - |
dc.contributor.author | Eichmann, George | - |
dc.contributor.other | Κασπαρής, Τάκης | - |
dc.date.accessioned | 2013-02-19T15:24:20Z | en |
dc.date.accessioned | 2013-05-17T05:30:09Z | - |
dc.date.accessioned | 2015-12-02T11:27:49Z | - |
dc.date.available | 2013-02-19T15:24:20Z | en |
dc.date.available | 2013-05-17T05:30:09Z | - |
dc.date.available | 2015-12-02T11:27:49Z | - |
dc.date.issued | 1986-10-15 | - |
dc.identifier.citation | Proceedings vol. 0638, Hybrid Image Processing, 1986, Orlando, United States | en_US |
dc.identifier.issn | 0277-786X | - |
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. Some 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 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. Experimental results will also be presented. | en_US |
dc.format | en_US | |
dc.language.iso | en | en_US |
dc.rights | © 1986 SPIE | en_US |
dc.subject | Image processing | en_US |
dc.subject | Classification | en_US |
dc.subject | Texture (Art) | en_US |
dc.title | Texture classification using the hough transform | en_US |
dc.type | Conference Papers | en_US |
dc.affiliation | City University of New York | en |
dc.collaboration | University of Central Florida | en_US |
dc.subject.category | Electrical Engineering - Electronic Engineering - Information Engineering | en_US |
dc.country | United States | en_US |
dc.subject.field | Engineering and Technology | en_US |
dc.publication | Peer Reviewed | en_US |
dc.relation.conference | SPIE Conference Proceedings | en_US |
dc.identifier.doi | 10.1117/12.964263 | en_US |
dc.dept.handle | 123456789/54 | en |
cut.common.academicyear | 2019-2020 | en_US |
item.openairetype | conferenceObject | - |
item.cerifentitytype | Publications | - |
item.fulltext | No Fulltext | - |
item.grantfulltext | none | - |
item.openairecristype | http://purl.org/coar/resource_type/c_c94f | - |
item.languageiso639-1 | en | - |
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: | Δημοσιεύσεις σε συνέδρια /Conference papers or poster or presentation |
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