Treffer: Visual characterization of paper using isomap and local binary patterns

Title:
Visual characterization of paper using isomap and local binary patterns
Authors:
TURTINEN, Markus, PIETIKÄIINEN, Matti, SILVEN, Olli
Source:
IEICE transactions on information and systems. 89(7):2076-2083
Publisher Information:
Oxford: Oxford University Press, 2006.
Publication Year:
2006
Physical Description:
print, 18 ref
Original Material:
INIST-CNRS
Subject Terms:
Electronics, Electronique, Computer science, Informatique, Telecommunications, Télécommunications, Sciences exactes et technologie, Exact sciences and technology, Sciences appliquees, Applied sciences, Informatique; automatique theorique; systemes, Computer science; control theory; systems, Intelligence artificielle, Artificial intelligence, Reconnaissance des formes. Traitement numérique des images. Géométrie algorithmique, Pattern recognition. Digital image processing. Computational geometry, Telecommunications et theorie de l'information, Telecommunications and information theory, Théorie de l'information, du signal et des communications, Information, signal and communications theory, Traitement du signal, Signal processing, Traitement des images, Image processing, Analyse texture, Texture analysis, Análisis textura, Concordance forme, Pattern matching, Inspection, Inspección, Papier, Paper, Papel, Vision ordinateur, Computer vision, Visión ordenador, Visualisation, Visualization, Visualización, paper inspection, texture analysis, visualization
Document Type:
Konferenz Conference Paper
File Description:
text
Language:
English
Author Affiliations:
Machine Vision Group, Department of Electrical and Information Engineering, University of Oulu, Finland
ISSN:
0916-8532
Access URL:
http://pascal-francis.inist.fr/vibad/index.php?action=search&terms=17982795
Rights:
Copyright 2006 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Computer science; theoretical automation; systems

Telecommunications and information theory
Accession Number:
edscal.17982795
Database:
PASCAL Archive

Weitere Informationen

In this paper, we study how a multidimensional local binary pattern (LBP) texture feature data can be visually explored and analyzed. The goal is to determine how true paper properties can be characterized with local texture features from visible light images. We utilize isometric feature mapping (Isomap) for the LBP texture feature data and perform non-linear dimensionality reduction for the data. These 2D projections are then visualized with original images to study data properties. Visualization is utilized in the manner of selecting texture models for unlabeled data and analyzing feature performance when building a training set for a classifier. The approach is experimented on with simulated image data illustrating different paper properties and on-line transilluminated paper images taken from a running paper web in the paper mill. The simulated image set is used to acquire quantitative figures on the performance while the analysis of real-world data is an example of semi-supervised learning.