Difference between revisions of "Publications:An Efficient Technique to Detect Visual Defects in Particleboards"
From ISLAB/CAISR
(Created page with "<div style='display: none'> == Do not edit this section == </div> {{PublicationSetupTemplate|Author=Jonas Guzaitis, Antanas Verikas |PID=236279 |Name=Guzaitis, Jonas (Departme...") |
|||
Line 4: | Line 4: | ||
{{PublicationSetupTemplate|Author=Jonas Guzaitis, Antanas Verikas | {{PublicationSetupTemplate|Author=Jonas Guzaitis, Antanas Verikas | ||
|PID=236279 | |PID=236279 | ||
− | |Name=Guzaitis, Jonas (Department of Applied Electronics, Kaunas University of Technology, Kaunas, Lithuania);Verikas, Antanas | + | |Name=Guzaitis, Jonas (Department of Applied Electronics, Kaunas University of Technology, Kaunas, Lithuania);Verikas, Antanas (av) (0000-0003-2185-8973) (Högskolan i Halmstad (2804), Akademin för informationsteknologi (16904), Halmstad Embedded and Intelligent Systems Research (EIS) (3938)) |
|Title=An Efficient Technique to Detect Visual Defects in Particleboards | |Title=An Efficient Technique to Detect Visual Defects in Particleboards | ||
|PublicationType=Journal Paper | |PublicationType=Journal Paper | ||
Line 26: | Line 26: | ||
|SeriesISSN= | |SeriesISSN= | ||
|ISBN= | |ISBN= | ||
− | |Urls= | + | |Urls=http://www.mii.lt/informatica/pdf/INFO726.pdf |
|ISRN= | |ISRN= | ||
|DOI= | |DOI= | ||
Line 55: | Line 55: | ||
|CreatedDate=2009-09-22 | |CreatedDate=2009-09-22 | ||
|PublicationDate=2009-09-22 | |PublicationDate=2009-09-22 | ||
− | |LastUpdated= | + | |LastUpdated=2015-03-16 |
|diva=http://hh.diva-portal.org/smash/record.jsf?searchId=1&pid=diva2:236279}} | |diva=http://hh.diva-portal.org/smash/record.jsf?searchId=1&pid=diva2:236279}} | ||
<div style='display: none'> | <div style='display: none'> |
Latest revision as of 22:42, 30 September 2016
Title | An Efficient Technique to Detect Visual Defects in Particleboards |
---|---|
Author | Jonas Guzaitis and Antanas Verikas |
Year | 2008 |
PublicationType | Journal Paper |
Journal | Informatica (Vilnius) |
HostPublication | |
Conference | |
DOI | |
Diva url | http://hh.diva-portal.org/smash/record.jsf?searchId=1&pid=diva2:236279 |
Abstract | This paper is concerned with the problem of image analysis based detection of local defects embedded in particleboard surfaces. Though simple, but efficient technique developed is based on the analysis of the discrete probability distribution of the image intensity values and the 2D discrete Walsh transform. Robust global features characterizing a surface texture are extracted and then analyzed by a pattern classifier. The classifier not only assigns the pattern into the quality or detective class, but also provides the certainty value attributed to the decision. A 100% correct classification accuracy was obtained when testing the technique proposed on a set of 200 images. |